Please join Anantha Chandrakasan, EECS Department Head for a "fireside chat" with Drew Houston, who will talk about innovation and entrepreneurship with Start6 participants.  TODAY, Jan. 27 at 3:00 PM in 34-101. Reception in lobby of building 34 to follow.

Computer Science and Artificial Intelligence Lab (CSAIL) and EECS graduate students Sang-Woo Jun and Ming Liu, working with Arvind, the Charles W. and Jennifer C. Johnson Professor of Electrical Engineering and Computer Science, have developed a storage system for big-data analytics that can dramatically decrease the time it takes to access information. The researchers, members of the CSAIL Computation Structures Group, will present the new system, which is based on a network of flash storage devices, at the International Symposium on Field-Programmable Gate Arrays in Monterey, Calif. in February.

Read more in the Jan. 31, 2014 MIT News Office article by Helen Knight titled "Storage system for ‘big data’ dramatically speeds access to information Using multiple nodes allows the same bandwidth and performance from a storage network as far more expensive machines," also posted below. [Photo left: BlueDBM — or Blue Database Machine — where each flash device is connected to a field-programmable gate array (FPGA) chip to create an individual node. Courtesy of researchers, MIT News Office.]

As computers enter ever more areas of our daily lives, the amount of data they produce has grown enormously.

But for this “big data” to be useful it must first be analyzed, meaning it needs to be stored in such a way that it can be accessed quickly when required.

Previously, any data that needed to be accessed in a hurry would be stored in a computer’s main memory, or dynamic random access memory (DRAM) — but the size of the datasets now being produced makes this impossible.

So instead, information tends to be stored on multiple hard disks on a number of machines across an Ethernet network. However, this storage architecture considerably increases the time it takes to access the information, according to Sang-Woo Jun, a graduate student in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT.

“Storing data over a network is slow because there is a significant additional time delay in managing data access across multiple machines in both software and hardware,” Jun says. “And if the data does not fit in DRAM, you have to go to secondary storage — hard disks, possibly connected over a network — which is very slow indeed.”

Now Jun, fellow CSAIL graduate student Ming Liu, and Arvind, the Charles W. and Jennifer C. Johnson Professor of Electrical Engineering and Computer Science, have developed a storage system for big-data analytics that can dramatically speed up the time it takes to access information.

The system, which will be presented in February at the International Symposium on Field-Programmable Gate Arrays in Monterey, Calif., is based on a network of flash storage devices.

Flash storage systems perform better at tasks that involve finding random pieces of information from within a large dataset than other technologies. They can typically be randomly accessed in microseconds. This compares to the data “seek time” of hard disks, which is typically four to 12 milliseconds when accessing data from unpredictable locations on demand.

Flash systems also are nonvolatile, meaning they do not lose any of the information they hold if the computer is switched off.

In the storage system, known as BlueDBM — or Blue Database Machine — each flash device is connected to a field-programmable gate array (FPGA) chip to create an individual node. The FPGAs are used not only to control the flash device, but are also capable of performing processing operations on the data itself, Jun says.

“This means we can do some processing close to where the data is [being stored], so we don’t always have to move all of the data to the machine to work on it,” he says.

What’s more, FPGA chips can be linked together using a high-performance serial network, which has a very low latency, or time delay, meaning information from any of the nodes can be accessed within a few nanoseconds. “So if we connect all of our machines using this network, it means any node can access data from any other node with very little performance degradation, [and] it will feel as if the remote data were sitting here locally,” Jun says.

Using multiple nodes allows the team to get the same bandwidth and performance from their storage network as far more expensive machines, he adds.

The team has already built a four-node prototype network. However, this was built using 5-year-old parts, and as a result is quite slow.

So they are now building a much faster 16-node prototype network, in which each node will operate at 3 gigabytes per second. The network will have a capacity of 16 to 32 terabytes.

Using the new hardware, Liu is also building a database system designed for use in big-data analytics. The system will use the FPGA chips to perform computation on the data as it is accessed by the host computer, to speed up the process of analyzing the information, Liu says.

“If we’re fast enough, if we add the right number of nodes to give us enough bandwidth, we can analyze high-volume scientific data at around 30 frames per second, allowing us to answer user queries at very low latencies, making the system seem real-time,” he says. “That would give us an interactive database.”

As an example of the type of information the system could be used on, the team has been working with data from a simulation of the universe generated by researchers at the University of Washington. The simulation contains data on all the particles in the universe, across different points in time.

“Scientists need to query this rather enormous dataset to track which particles are interacting with which other particles, but running those kind of queries is time-consuming,” Jun says. “We hope to provide a real-time interface that scientists can use to look at the information more easily.”

Kees Vissers of programmable chip manufacturer Xilinx, based in San Jose, Calif., says flash storage is beginning to be seen as a replacement for both DRAM and hard disks. “Historically, computer architecture had to have a particular memory hierarchy — cache on the processors, DRAM off-chip, and then hard disks — but that whole line is now being blurred by novel mechanisms of flash technology.”

The work at MIT is particularly interesting because the team has optimized the whole system to work with flash, including the development of novel hardware interfaces, Vissers says. “This means you get a system-level benefit,” he says.

in MIT's Research Laboratory of Electronics (RLE), has been selected for a CAREER Award from the National Science Foundation in support of work 

Timothy K. Lu, Assistant Professor leading the Synthetic Biology Group in the Department of Electrical Engineering and Computer Science and Department of Biological Engineering and principal investigator 

to understand biological cells as state machines leading to insights into natural biological systems and synthetic gene circuits. The work will lead to shared online resources for the wider scientific community and the continued development of a new course Biological Circuit engineering Laboratory (BioCEL) to educate multiple levels (high school, community college and university) at the intersection of biology and engineering. See the NSF award site.

Tim received his S.B. And M.Eng. in Electrical Engineering and Computer Science at MIT and completed his M.D./Ph.D. training in the Harvard-MIT Health Sciences and Technology Program. He is a core member of the Synthetic Biology Center at MIT, Associate Member at the Broad Institute of MIT and Harvard, and co-founder of Sample6 Technologies. He is also affiliated with the MIT CSBi Program, the MIT Microbiology Program, and the Harvard Biophysics Program.

Tim has pioneered new approaches to combat infectious diseases with synthetic biology, encode memory in the DNA of living cells, and perform both digital and analog computation in biological systems. His group’s research focuses on engineering fundamental technologies to enable the scalable design of biological systems and on applying synthetic biology to solve medical and industrial problems. Tim is a recipient of the Henry L. and Grace Doherty Professorship, NIH New Innovator Award, Lemelson-MIT Student Prize for Invention, Army Young Investigator Award, Ellison New Scholar in Aging Award, and Presidential Early Career Award for Scientists and Engineers (PECASE).

MIT President L. Rafael Reif announced to the MIT community the permanent appointments of two longtime members of the MIT community to provost and chancellor. Martin A. Schmidt, a faculty member of the MIT Electrical Engineering and Computer Science Department since 1988, and director of the Microsystems Technology Laboratories (MTL) from 1999 to 2006, has served as associate provost since 2008 and recently Acting Provost. (Read more about Martin Schmidt at his website.) President Reif's announcement also included the appointment of Associate Dean in the MIT School of Engineering Cynthia Barnhardt as MIT Chancellor, succeeding W. Eric Grimson, who served as MIT Chancellor from 2011 until his appointment in Oct. 2013 as Chancellor of Academic Advancement. [Photo right: Martin A. Schmidt, MIT Provost, Cynthia Barnhardt, MIT Chancellor. Courtesy of MIT News Office, Dominic Reuter, photographer]

Read more in the Feb. 3, 2014 MIT News announcement by Steve Bradt titled "Martin Schmidt named provost; Cynthia Barnhart named chancellor Two faculty members named to MIT’s most senior academic posts first arrived at the Institute as students in the early 1980s.," also posted below in its entirety.

Two longtime members of the faculty — who first arrived at MIT in the early 1980s as graduate students — have been named provost and chancellor, the Institute’s two most senior academic posts.

Martin Schmidt, an electrical engineering professor who has served as associate provost since 2008 and as acting provost since last fall, has been named provost on a permanent basis, President L. Rafael Reif announced this morning in an email to the MIT community.

Reif also announced that Cynthia Barnhart, a professor in the Department of Civil and Environmental Engineering, is MIT’s new chancellor. Barnhart has been associate dean of the School of Engineering since 2007; she served as interim dean of engineering from 2010 to 2011.

Schmidt’s appointment as provost, MIT’s senior academic and budget officer, and Barnhart’s appointment as chancellor, with overarching responsibility for graduate and undergraduate education and student life, are both effective immediately.

Provost Martin Schmidt

Martin Schmidt, 54, is a professor of electrical engineering. As associate provost, he has played key roles in the allocation of physical space on campus; in co-leading the Institute-Wide Planning Task Force, which shaped MIT’s response to the global financial crisis; and in developing MIT’s plans for the future of Kendall Square.

“Marty brings to the role of provost a powerful combination of skills and experience as a teacher, advisor, administrator, researcher, inventor and entrepreneur,” Reif wrote in his letter, adding: “Marty has cheerfully accepted and successfully handled a great many sensitive, difficult assignments for the MIT community. In the process, he has become well known, inside and outside MIT, for his clarity, integrity, strategic perspective and ability to bring people together to get hard things done.”

“In three months as Acting Provost, Marty has proved himself an indispensable member of our senior team,” Reif wrote, “and I am delighted that he has accepted my offer to help lead MIT as provost.”

Schmidt says that his tenure as associate provost — and as director of MIT’s Microsystems Technology Laboratories (MTL) from 1999 to 2006 — has broadened his appreciation of the Institute, stoking an intellectual curiosity that attracts him to his new, more expansive role.

“I find great joy in learning about new fields,” Schmidt says. “What I find most exciting about the opportunity to serve as MIT’s provost is the intellectual stimulation that I know will come from engaging with all the diverse parts of this extraordinary institution.”

A native of Mountain Top, Pa., Schmidt has been at MIT since 1981, when he arrived to pursue graduate studies in the Department of Electrical Engineering and Computer Science (EECS). He earned his SM in 1983 — largely for research conducted at Lincoln Laboratory — and his PhD in 1988.

“I’ve always been interested in making things — since my teenage years, when I would rebuild cars or build furniture,” says Schmidt, who arrived at MIT, fresh from receiving his BS in electrical engineering at Rensselaer Polytechnic Institute, with a strong interest in integrated circuits. “When I came to MIT, the frontiers of my field were in microelectronics — the drive to make transistors smaller and smaller. But I soon became aware of the potential to apply miniaturization elsewhere.”

Recognizing that the skills he had honed for microelectronics could be useful in other fields, Schmidt broadened his horizons as a graduate student, turning to miniature sensors for use in factories or vehicles. (At the time, sensors governing airbag deployment were a hot topic.) He later conducted research on sensors to detect turbulence, with a mentor from the Department of Aeronautics and Astronautics who ultimately co-supervised his doctoral thesis on the topic.

When Schmidt joined the MIT faculty as an assistant professor upon earning his PhD, his enthusiasm for interdisciplinary collaboration drew him to partner with colleagues outside EECS, and even outside MIT. Attracted to problems with practical applications, he also found himself working closely with industrial collaborators: with 3M on miniature sensors for monitoring plastic processing, with Bosch on micromachined valves, and with General Motors on crash sensors, among others. He holds more than 30 issued U.S. patents.

“I’m a guy who knows how to make small things, for whatever applications they may be useful in,” Schmidt says. “I enjoy working on these devices until they are ready for commercialization. At that point, the research problem starts to feel too constrained, and I look to move on as the guardrails close in.”

Drawing on his extensive experience as an inventor and entrepreneur, Schmidt served on MIT’s commission on Production in the Innovation Economy; in 2011, when the White House asked MIT to help drive its Advanced Manufacturing Partnership, it was a natural next step for Schmidt to serve as faculty lead. The following year, Schmidt was appointed to oversee two of MIT’s industry-facing offices, the Technology Licensing Office and the Office of Corporate Relations. More recently, he championed and helped to shape MIT’s new Innovation Initiative.

Schmidt’s entrepreneurship has its roots in the 1990s, when he cultivated an interest in microfluidics. He began a lengthy collaboration with Klavs Jensen, a professor with joint appointments in chemical engineering and in materials science and engineering, to develop miniature chemical reactors. The resulting devices, roughly half a cubic centimeter in size, burn fuel at temperatures of 700 to 800 degrees Celsius — but when surrounded by an insulating chip, are safe to the touch. This yields a handheld reactor that, when merged with a solid-oxide fuel cell, can convert chemical fuel to electricity.

The effort gave rise to startup Lilliputian Systems, launched in 2002, one of six companies Schmidt has had a role in starting. Two others grew out of microfluidics research with a pair of biomedically oriented colleagues, Martha Gray and Mehmet Toner, that allowed the manipulation of individual cells in blood. One of these companies — Living Microsystems, later renamed Verinata Health, and purchased last year by Illumina — developed a test for prenatal screening based upon a maternal blood draw, eliminating the need for amniocentesis.

“Each stage of my career at MIT has exposed me to new communities within MIT and new ways of thinking about the world and the work of the Institute,” Schmidt says. “When I began collaborating with chemical engineers, I learned an entirely new way of thinking about engineering. Similarly, to lead MTL, I had to explore the work of everyone in the lab. As associate provost, my role in allocating physical space gave me a unique perspective on the distinctive needs of every part of MIT, and my involvement in the Institute’s response to the global financial crisis represented an intensive education in MIT’s financial operations.”

The provost is MIT’s senior academic and budget officer, with overall responsibility for the Institute’s educational programs, as well as for the recruitment, promotion, and tenuring of faculty. As provost, Schmidt will work closely with the deans of MIT’s five schools to establish academic priorities, and with Executive Vice President and Treasurer Israel Ruiz to manage the financial planning to support these priorities. The provost also oversees the Institute’s library system and works with Vice President for Research Maria Zuber to coordinate support for research priorities.

As provost, Schmidt succeeds Professor of Biology Chris A. Kaiser, who stepped down last fall to return to teaching and research. Reif’s selection of Schmidt — following consultation with many members of the faculty, as well as students — was enthusiastically endorsed by the Executive Committee of the MIT Corporation. Reif also considered the input of members of the MIT community who submitted comments and suggestions.

Schmidt and his wife of 27 years, Lyn, who is active in volunteer organizations, live in Reading. They have four sons: Derek, who works for State Street Corporation; Brian, a senior at the University of Connecticut; Kevin, a freshman at the University of Maine; and Danny, a senior at Reading Memorial High School.

Chancellor Cynthia Barnhart

Cynthia Barnhart, 54, is the Ford Foundation Professor of Engineering, with an appointment in the Department of Civil and Environmental Engineering and a joint appointment in the Engineering Systems Division. She has been associate dean of the School of Engineering since 2007, working closely with the dean of engineering on major areas of responsibility including tenure and promotion, budgets, strategic planning, and the day-to-day operations of MIT’s largest school. She served as interim dean of the School of Engineering from July 2010 to January 2011.

As associate dean, Barnhart has held primary responsibility for overseeing faculty searches, ensuring that hiring practices achieve the highest possible faculty quality and diversity. She also chaired the School of Engineering Education Council, working to facilitate teaching and learning across disciplines, and led committees that developed policies that have increased flexibility in dual faculty appointments and established guidelines for faculty mentoring in the School of Engineering.

“A clear-eyed problem-solver in the classic MIT tradition, Cindy was drawn to MIT by our culture of approaching hard problems by thinking across disciplines and Schools,” Reif wrote in his letter to the MIT community, noting that “Cindy has coupled her academic achievements with wide-ranging service to MIT.”

“Cindy comes to the chancellorship with a lively awareness of the demands and realities of student life on campus,” Reif added. “In interviewing for this position, she explained to me that from the start of her time on the faculty — a job she began when her first child was three weeks old — she has made a conscious effort to prove that it is possible to have both a successful career and a satisfying family life; her commitment and her example on this score will be tremendously useful in helping our famously intense community strike a productive balance.”

MIT’s chancellor oversees graduate and undergraduate education, student life, student services, and other areas with impact on the student experience. The deans of graduate education, undergraduate education, and student life all report to the chancellor; the Office of Digital Learning reports to both the chancellor and the provost. Together with the provost, the chancellor advises the president and participates in strategic planning on faculty appointments, resource development, and Institute resources and buildings. “I’m thrilled to have the opportunity to serve as chancellor,” Barnhart says, “because the position is all about students and their learning and life experiences at MIT. I can think of nothing on our campus more important to me.”

Barnhart has served as an undergraduate adviser every year since 1992, and has supervised 83 graduate and undergraduate theses of students in the departments of Civil and Environmental Engineering, Aeronautics and Astronautics, Mechanical Engineering, and Electrical Engineering and Computer Science; in the Engineering Systems Division; and in the MIT Sloan School of Management. She has taught courses on large-scale optimization, airline operations research, the global airline industry, and transportation operations, planning, and control.

The mother of two daughters, both in college, Barnhart says, “MIT students are, of course, unbelievably smart. I love the way they think, and how they so often teach me something unexpected. I look forward to spending as much time as I can learning from them in this new role.”

Barnhart is a native of Barre, Vt. After earning her BS from the University of Vermont in 1981, she spent two years at the engineering firm Bechtel, where she worked as a planning and scheduling engineer for the Metro subway system in Washington, D.C. She arrived at MIT in 1984 to pursue graduate work in transportation and operations research, earning her SM in transportation in 1985 and her PhD in 1988.

“I came to MIT because its programs weren’t siloed; they were highly interdisciplinary, even in the 1980s,” Barnhart says. “I had the entire Institute at my fingertips. The barriers between departments are low and porous here. When you’re at MIT, you’re at MIT — the whole place.”

After earning her degrees, Barnhart took a faculty job at the Georgia Institute of Technology for four years before rejoining MIT as an assistant professor in 1992. She became an associate professor in 1995 and a full professor in 2002.

She served as co-director of the Center for Transportation and Logistics from 2001 to 2003, and has served twice as co-director of MIT’s Operations Research Center, from 1999 to 2002 and from 2006 to 2010. Since 2009, she has also served as the director of Transportation@MIT, an interdisciplinary initiative that integrates the work of hundreds of faculty members to invent new technologies and innovative systems to meet the growing global demand for mobility.

Barnhart, a member of the National Academy of Engineering, focuses her research on optimizing transportation systems, especially in aviation. She develops mathematical models and algorithms, often context- and data-driven, to shape the design of transportation systems. She has advised domestic and international airlines on schedule design and resource utilization, and the Federal Aviation Administration on policies to improve the U.S. aviation system overall, particularly on topics around congestion and delays.

Among other findings, Barnhart’s modeling has shown that using administrative controls or market mechanisms to limit the number of scheduled flights to airport capacity — practices not currently used in scheduling flights at most U.S. airports — could significantly reduce passenger delays while boosting airline profits.

“I enjoy problems that can be subjected to rigorous analysis, but that have no one right answer,” Barnhart says. “There is a blending of art and science in building optimization models; the art is capturing a real-world problem with a mathematical model, and the science is devising approaches to solve it.”

Barnhart succeeds former Chancellor W. Eric Grimson, who left the post to assume a new role in MIT’s upcoming fundraising campaign. She was selected as chancellor following a process of consultation with MIT faculty, staff, and students. The Institute’s Undergraduate Association (UA) and Graduate Student Council (GSC) created an eight-member Chancellor Search Advisory Cabinet to advise Reif; the president also received input from the students nominated by the UA and GSC to serve on a Presidential Advisory Cabinet, which advises him on a range of student issues. Reif also met with faculty and staff to hear their thoughts on the qualities and attributes most important in a new chancellor. Finally, Reif’s selection of Barnhart was enthusiastically endorsed by the Executive Committee of the MIT Corporation.

In the coming months, Barnhart plans to set her priorities as chancellor by meeting with students in formal and informal settings. “I want to make the student experience at MIT as positive and fulfilling as possible,” she says, “and I look forward to engaging fully with students to make that happen.”

Barnhart and her husband, Mark Baribeau, managing director and head of global equities at Jennison Associates, live in Wellesley. They have two daughters: Olivia, a senior at Colby College, and Julia, a freshman at Santa Clara University.

Srini Devadas has been selected to receive the IEEE Computer Society’s 2014 Technical Achievement Award “For pioneering work in secure hardware, including the invention of Physical Unclonable Functions and single-chip secure processor architectures.” The IEEE Computer Society Technical Achievement Award is given for outstanding and innovative contributions to the fields of computer and information science and engineering or computer technology, usually within the past 10, and not more than 15, years. Prof. Devadas will formally receive this award in June at the IEEE award ceremony in Seattle.

Professor Devadas was one of the first to recognize that manufacturing variations in integrated circuits could be used to not just identify, but to authenticate, individual integrated circuits. He coined the term Physical Unclonable Functions (PUFs) in 2002; PUFs are now a very active field of research and this technology has been commercialized for use in anti-counterfeiting applications. His 2003 paper co-authored with his students on Aegis, one of the first single-chip secure processors, will be included in “25 Years of the International Conference on Supercomputing (ICS)”, a volume which recognizes the most influential papers published in ICS between 1987-2011. He received the 2014 ASPLOS Most Influential Paper Award for a paper on hardware information flow tracking— a paper which he co-authored with his students in the Architectural Support for Programming Languages and Operating Systems (ASPLOS) conference in 2004. Recent work with students and collaborators on Oblivious RAM received a Best Student Paper Award at the Computer and Communications Security conference in 2013.

6.041, Introduction to Probability has been offered in the EECS Department for decades. This term (ST2014) Professors John Tsitsiklis and Patrick Jaillet will teach the subject in a much wider context and to a much wider class — with roughly 18 to 20,000 students as part of MITx.

Read more in the January 29, 2014 MIT News Office article by Sara Sezun and Steve Carson (Office of Digital Learning) titled "MITx course builds a systematic approach to understanding the uncertain. 6.041x shows learners how to use probability to make scientifically sound predictions under uncertainty," also posted below in its entirety.

Many aspects of our personal and professional lives are fraught with uncertainty. Should we invest in the stock market now, or wait? How reliable are the GPS readings on a smartphone? What is the likelihood that a medical treatment will be effective? Through the new MITx course 6.041x (Introduction to Probability – The Science of Uncertainty), MIT professors John Tsitsiklis and Patrick Jaillet share the probabilistic models used to analyze these and many other uncertain situations.

While the course was developed in the Department of Electrical Engineering and Computer Science (EECS) over many decades, Tsitsiklis says the course is relevant to a much wider audience: "The class is targeted not just to EE (Electrical Engineering) students. For example, biologists need probability tools more and more."

Tsitsiklis, the Clarence J Lebel Professor of Electrical Engineering, also describes his course’s approach as unique: “We’re more ambitious than the typical undergraduate probability class. We’re different from a class that gives an overview of problems and ideas ... We aim to provide the crispest way of explaining the concepts.”

He explains that the ability to think probabilistically is a fundamental component of scientific literacy. Students in 6.041x will learn the models, skills, and tools that are the keys to analyzing data and making scientifically sound predictions under uncertainty.

Tsitsiklis is intrigued by teaching through a new medium, which may appeal to students with various learning styles. “Some people prefer to learn by reading a textbook ... Some want the encouragement of chatting with an instructor. We hope this medium (MITx) will be perfect for some people.”

The online class will offer the same content as the residential class. Tsitsiklis, who is also associate director of the Laboratory for Information and Decision Systems, has done most of the course development, while Jaillet, the Dugald C. Jackson Professor of EECS, will be responsible for managing the course once it begins. In addition, a teaching assistant, along with two undergraduates, will monitor the class forum, prepared to answer students’ questions as necessary.

6.041x will be divided into 26 lectures, of which 23 will be given by Tsitsiklis, and three will be given by Jaillet. Each lecture is divided into eight to 10 short video clips, interspersed with concept questions and simple exercises. “It will be like doing mini-homework during class,” Tsitsiklis says. “Students will have to solve the problems on the spot,” which will provide them immediate feedback. In addition, students will have access to problem-solving videos, mostly recorded by MIT graduate students, that correspond to the recitations and tutorials in the residential course.

Tsitsiklis emphasized that 6.041x will be as challenging as the residential course. “We have decided to keep it at exactly the same level,” he says, adding that the lectures will cover the same material, and students will be required to have a year of college-level calculus. “We have made the decision that this will be an ambitious, complete class, instead of a watered-down version.”

The textbook for the course, "Introduction to Probability" (2008, Athena Scientific), was co-written by Tsitsiklis and Professor Dimitri Bertsekas, the McAfee Professor of Electrical Engineering. Students will be given free online access through the edX platform, and offered a discount for purchase of a hard copy of the text.

Thus far, 18,000 people have registered to take 6.041x. Tsitsiklis expects that at least 20,000 will eventually take the course. Whether or not students complete all of the homework and tests, he still welcomes their participation. “Let everyone follow as much as they wish. It’s fine if people just want to listen and learn something," he says.

Researchers at MIT’s Microsystems Technology Laboratory (MTL) including Anantha Chandrakasan, the Joseph F. and Nancy P. Keithley Professor of Electrical Engineering, recent EECS PhD graduate Marcus Yip, EECS graduate student Rui Jin and research scientist Nathan Ickes, together with physicians from Harvard Medical School and the Massachusetts Eye and Ear Infirmary (MEEI), have developed a new, low-power signal-processing chip that could lead to a cochlear implant that requires no external hardware. The implant would be wirelessly recharged -- taking just two minutes -- and would run for about eight hours on each charge.  The researchers are presenting their work this week at the International Solid-State Circuits Conference in San Francisco.

Read more in the Feb. 9, 2014 MIT News Office article by Larry Hardesty titled "Cochlear implants — with no exterior hardware - A cochlear implant that can be wirelessly recharged would use the natural microphone of the middle ear rather than a skull-mounted sensor," also posted below in its entirety.

Cochlear implants — medical devices that electrically stimulate the auditory nerve — have granted at least limited hearing to hundreds of thousands of people worldwide who otherwise would be totally deaf. Existing versions of the device, however, require that a disk-shaped transmitter about an inch in diameter be affixed to the skull, with a wire snaking down to a joint microphone and power source that looks like an oversized hearing aid around the patient’s ear.

Researchers at MIT’s Microsystems Technology Laboratory (MTL), together with physicians from Harvard Medical School and the Massachusetts Eye and Ear Infirmary (MEEI), have developed a new, low-power signal-processing chip that could lead to a cochlear implant that requires no external hardware. The implant would be wirelessly recharged and would run for about eight hours on each charge.

The researchers describe their chip in a paper they’re presenting this week at the International Solid-State Circuits Conference. The paper’s lead author — Marcus Yip, who completed his PhD at MIT last fall — and his colleagues Rui Jin and Nathan Ickes, both in MIT’s Department of Electrical Engineering and Computer Science, will also exhibit a prototype charger that plugs into an ordinary cell phone and can recharge the signal-processing chip in roughly two minutes.

“The idea with this design is that you could use a phone, with an adaptor, to charge the cochlear implant, so you don’t have to be plugged in,” says Anantha Chandrakasan, the Joseph F. and Nancy P. Keithley Professor of Electrical Engineering and corresponding author on the new paper. “Or you could imagine a smart pillow, so you charge overnight, and the next day, it just functions.”

Adaptive reuse

Existing cochlear implants use an external microphone to gather sound, but the new implant would instead use the natural microphone of the middle ear, which is almost always intact in cochlear-implant patients.

The researchers’ design exploits the mechanism of a different type of medical device, known as a middle-ear implant. Delicate bones in the middle ear, known as ossicles, convey the vibrations of the eardrum to the cochlea, the small, spiral chamber in the inner ear that converts acoustic signals to electrical. In patients with middle-ear implants, the cochlea is functional, but one of the ossicles — the stapes — doesn’t vibrate with enough force to stimulate the auditory nerve. A middle-ear implant consists of a tiny sensor that detects the ossicles’ vibrations and an actuator that helps drive the stapes accordingly.

The new device would use the same type of sensor, but the signal it generates would travel to a microchip implanted in the ear, which would convert it to an electrical signal and pass it on to an electrode in the cochlea. Lowering the power requirements of the converter chip was the key to dispensing with the skull-mounted hardware.

Chandrakasan’s lab at MTL specializes in low-power chips, and the new converter deploys several of the tricks that the lab has developed over the years, such as tailoring the arrangement of low-power filters and amplifiers to the precise acoustic properties of the incoming signal.

But Chandrakasan and his colleagues also developed a new signal-generating circuit that reduces the chip’s power consumption by an additional 20 to 30 percent. The key was to specify a new waveform — the basic electrical signal emitted by the chip, which is modulated to encode acoustic information — that is more power-efficient to generate but still stimulates the auditory nerve in the appropriate way.

Verification

The waveform was based on prior research involving simulated nerve fibers, but the MIT researchers tailored it for cochlear implants and found a low-power way to implement it in hardware. Two of their collaborators at MEEI — Konstantina Stankovic, an ear surgeon who co-led the study with Chandrakasan, and Don Eddington — tested it on four patients who already had cochlear implants and found that it had no effect on their ability to hear. Working with another collaborator at MEEI, Heidi Nakajima, the researchers have also demonstrated that the chip and sensor are able to pick up and process speech played into a the middle ear of a human cadaver.

“It’s very cool,” says Lawrence Lustig, director of the Cochlear Implant Center at the University of California at San Francisco. “There’s a much greater stigma of having a hearing loss than there is of having a visual loss. So people would be very keen on losing the externals for that reason alone. But then there’s also the added functional benefit of not having to take it off when you’re near water or worrying about components getting lost or broken or stolen. So there are some important practical considerations as well.”

Lustig points out that the new cochlear implant would require a more complex surgery than existing implants do. “A current cochlear-implant operation takes an hour, hour and a half,” he says. “My guess is that the first surgeries will take three to four hours.” But he doubts that that would be much of an obstacle to adoption. “As we get better and better and better, that time will shorten,” he says. “And three to four hours is still a relatively straightforward operation. I don’t anticipate putting a lot of extra risk into the procedure.”

Electrical Engineering and Computer Science Department Head Anantha Chandrakasan and Associate Department Heads David Perreault and Bill Freeman announced the promotions of Professors Manolis Kellis, Collin Stultz, and Ron Weiss to the rank of Full Professor, and of Professor Timothy Lu to the rank of Associate Professor without Tenure, effective July 1, 2014. Brief descriptions of their work appear below. Congratulations!

	Prof. Manolis Kellis develops algorithms and computational techniques to understand the human genome and to find the mechanisms relating human genetic information to human disease. His research has charted the functional elements and circuitry of the human genome, using comparative genomics, epigenomics, and regulatory genomics, and now forms the foundation of countless genomic and genetic studies. Prof. Kellis is internationally recognized for his work, with more than a hundred journal publications, and has received numerous awards. He runs a very large and highly productive research group, and is an excellent mentor to his students and post-docs, and a highly regarded teacher. He often takes a leadership role within large collaborations that span computational and experimental work across many institutions, and is seen as a star in this key area of 21st century biology.
	A leader in his field, Prof. Collin Stultz uses techniques drawn from computational chemistry, signal processing and biochemistry to study the molecular mechanisms underlying human disease pathogenesis. Through computer modeling, he has developed a paradigm-shifting framework for understanding how collagen is degraded, implicated in the pathogenesis of atherosclerosis, rheumatoid arthritis, and cancer. He uses Bayesian methods to characterize the conformations of intrinsically disordered proteins, known to play a central role in neurological disorders, such as Alzheimer’s and Parkinson’s disease. Among his honors are being a recipient of the Burroughs Wellcome Fund Career Award in Biomedical Sciences and the James Tolbert Shipley Prize. A practicing cardiologist, he leads the biomedical area of EECS, and co-developed 6.S02, Introduction to EECS II from a Medical Technology Perspective.
	Prof. Ron Weiss a world leader in the field of synthetic biology, is noted for his development of systematic engineering methodology in the nascent field. He has designed and constructed synthetic networks in bacteria, yeast, and mammalian cells, which in particular may lead to revolutionary medical applications. His group developed synthetic biological systems that sense and destroy cancer cells by detecting diagnostic miRNA signatures, and gene circuits that control stem cell differentiation into pancreatic beta cells for diabetes as well as other cell types. He founded and co-directs the MIT Synthetic Biology Center, and takes a leading educational role, developing new classroom subjects and coaching the undergraduate iGEM Competition.
	Prof. Timothy K. Lu is a rising star in the field of synthetic biology. His contributions to synthetic biology include the development of integrated digital logic, memory, and analog computation in living cells, and the translation of engineered virus technology for next-generation bacteriophage for antibiotic-resistant bacteria. Prof. Lu is the winner of many prestigious awards, including the Presidential Early Career Award for Scientists and Engineers (PECASE) 2012, and was named to the “Top Young Innovators under 35” list by Technology Review, 2010. Prof. Lu is an excellent teacher who is making great contributions to our curriculum through the development of a major lab-oriented course in synthetic biology.

Computer Science and Artificial Intelligence Lab's Leslie Kaelbling, the Panasonic Professor of Electrical Engineering and Computer Science in collaboration with members of her research group the Learning and Intelligent Systems Group have developed a new way to use "multiagent systems" to allow for teams of robots to accomplish tasks requiring flexibility and communication in uncertain environments. The team including postdocs (and first and second authors, respectively) Christopher Amato and George Konidares will present their work titled "Planning with Macro-Actions in Decentralized POMDPs" at the International Conference on Autonomous Agents and Multiagent Systems in May.

Read more in the Feb. 12, 2014 MIT News Office article by Larry Hardesty titled "Herding robots - A new system combines simple control programs to enable fleets of robots — or other “multiagent systems” — to collaborate in unprecedented ways," also posted below in its entirety.

Writing a program to control a single autonomous robot navigating an uncertain environment with an erratic communication link is hard enough; write one for multiple robots that may or may not have to work in tandem, depending on the task, is even harder.

As a consequence, engineers designing control programs for “multiagent systems” — whether teams of robots or networks of devices with different functions — have generally restricted themselves to special cases, where reliable information about the environment can be assumed or a relatively simple collaborative task can be clearly specified in advance.

This May, at the International Conference on Autonomous Agents and Multiagent Systems, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) will present a new system that stitches existing control programs together to allow multiagent systems to collaborate in much more complex ways. The system factors in uncertainty — the odds, for instance, that a communication link will drop, or that a particular algorithm will inadvertently steer a robot into a dead end — and automatically plans around it.

For small collaborative tasks, the system can guarantee that its combination of programs is optimal — that it will yield the best possible results, given the uncertainty of the environment and the limitations of the programs themselves.

Working together with Jon How, the Richard Cockburn Maclaurin Professor of Aeronautics and Astronautics, and his student Chris Maynor, the researchers are currently testing their system in a simulation of a warehousing application, where teams of robots would be required to retrieve arbitrary objects from indeterminate locations, collaborating as needed to transport heavy loads. The simulations involve small groups of iRobot Creates, programmable robots that have the same chassis as the Roomba vacuum cleaner.

Reasonable doubt

“In [multiagent] systems, in general, in the real world, it’s very hard for them to communicate effectively,” says Christopher Amato, a postdoc in CSAIL and first author on the new paper. “If you have a camera, it’s impossible for the camera to be constantly streaming all of its information to all the other cameras. Similarly, robots are on networks that are imperfect, so it takes some amount of time to get messages to other robots, and maybe they can’t communicate in certain situations around obstacles.”

An agent may not even have perfect information about its own location, Amato says — which aisle of the warehouse it’s actually in, for instance. Moreover, “When you try to make a decision, there’s some uncertainty about how that’s going to unfold,” he says. “Maybe you try to move in a certain direction, and there’s wind or wheel slippage, or there’s uncertainty across networks due to packet loss. So in these real-world domains with all this communication noise and uncertainty about what’s happening, it’s hard to make decisions.”

The new MIT system, which Amato developed with co-authors Leslie Kaelbling, the Panasonic Professor of Computer Science and Engineering, and George Konidaris, a fellow postdoc, takes three inputs. One is a set of low-level control algorithms — which the MIT researchers refer to as “macro-actions” — which may govern agents’ behaviors collectively or individually. The second is a set of statistics about those programs’ execution in a particular environment. And the third is a scheme for valuing different outcomes: Accomplishing a task accrues a high positive valuation, but consuming energy accrues a negative valuation.

School of hard knocks

Amato envisions that the statistics could be gathered automatically, by simply letting a multiagent system run for a while — whether in the real world or in simulations. In the warehousing application, for instance, the robots would be left to execute various macro-actions, and the system would collect data on results. Robots trying to move from point A to point B within the warehouse might end up down a blind alley some percentage of the time, and their communication bandwidth might drop some other percentage of the time; those percentages might vary for robots moving from point B to point C.

The MIT system takes these inputs and then decides how best to combine macro-actions to maximize the system’s value function. It might use all the macro-actions; it might use only a tiny subset. And it might use them in ways that a human designer wouldn’t have thought of.

Suppose, for instance, that each robot has a small bank of colored lights that it can use to communicate with its counterparts if their wireless links are down. “What typically happens is, the programmer decides that red light means go to this room and help somebody, green light means go to that room and help somebody,” Amato says. “In our case, we can just say that there are three lights, and the algorithm spits out whether or not to use them and what each color means.”

The MIT researchers’ work frames the problem of multiagent control as something called a partially observable Markov decision process, or POMDP. “POMDPs, and especially Dec-POMDPs, which are the decentralized version, are basically intractable for real multirobot problems because they’re so complex and computationally expensive to solve that they just explode when you increase the number of robots,” says Nora Ayanian, an assistant professor of computer science at the University of Southern California who specializes in multirobot systems. “So they’re not really very popular in the multirobot world.”

“Normally, when you’re using these Dec-POMDPs, you work at a very low level of granularity,” she explains. “The interesting thing about this paper is that they take these very complex tools and kind of decrease the resolution.”

“This will definitely get these POMDPs on the radar of multirobot-systems people,” Ayanian adds. “It’s something that really makes it way more capable to be applied to complex problems.”

Each year, the Dan David Foundation, headquartered at Tel Aviv University, selects a laureate — for each of three time dimensions past, present and future — who represents the culmination of innovative and interdisciplinary research that fosters universal values and goals promoting outstanding scientific, technological, cultural or social achievements that improve the world.

This year the Dan David Foundation International Board selected Marvin Minsky to receive the Dan David Foundation Prize for the Future Time Dimension titled “Artificial Intelligence: The Digital Mind. Prof. Minsky was selected as one of the founders of the field of artificial intelligence. He is cited as among the most influential intellectuals of the twentieth century in a variety of disciplines, including AI, robotics, computation, learning, cognition, philosophy and optics.

Marvin Minsky, the Toshiba Professor of Media Arts and Sciences and Professor of Electrical Engineering and Computer Science at MIT has made his professional life at MIT since 1957, founding the MIT Artificial Intelligence Project in 1959, serving as Co-Director of the MIT Artificial Intelligence Laboratory from 1959 to 1974, and serving as the Donner Professor of Science at MIT from 1974 to 1989. He became the Toshiba professor of Media Arts and Sciences in 1990.

Pioneering robotics and telepresence, Minsky is recognized for his work using computational ideas to characterize human psychological processes – and working to endow machines with intelligence. His early 1960s papers “Steps Towards Artificial Intelligence,” “Matter, Mind, and Models,” and (with Seymour Papert) “Perceptrons” placed Prof. Minsky in the forefront of the new field of Artificial Intelligence. With Papert, Minsky proposed a new theory they called “The Society of Mind” – combining developments from child psychology with their research on Artificial Intelligence to address the complexity of intelligence.

Minsky continued to develop this theory through the next decade, publishing in 1985 a book of the same title and proposing individual mechanisms to account for a matching psychological phenomenon. He proposed theories to account for human higher-level feelings and uniquely human resourcefulness in the sequel, “The Emotion Machine.”

Prof. Minsky has received numerous awards including the ACM Turing Award in 1970, the IEEE Computer Society Computer Pioneer Award in 1995 and the Benjamin Franklin Medal from the Franklin Institute in 2001. He is a member of the National Academy of Engineering and the National Academy of Sciences, and many other societies. He completed his PhD dissertation at Princeton University in 1954. It was titled “neural nets and the Brain Model Problem.”  This represented the first publication of theories and theorems about learning in neural networks, secondary reinforcement, circulating dynamic storage and synaptic modifications.

Read about the 2014 Dan David Prizes in the Jerusalem Post.

Last week, computer science luminaries - including seven Turing Award winners and Eric Schmidt, Google’s former CEO and current executive chairman - either attended or contributed appreciations in celebration of the 70th birthday of Butler Lampson, adjunct professor at MIT since 1987 and a technical fellow at Microsoft Research. As one of the founders of Xerox’s Palo Alto Research Center (PARC), Lampson helped create the Alto, the first computer to feature a mouse and a graphical user interface (GUI) — the progenitor of both the Apple Macintosh and the Windows operating system. He also led the development of Bravo, the first “what you see is what you get” — or WYSIWYG — word processor, which ran on the Alto. (Lampson is one of the seven Turing Award winners at last week's celebration!)

Read more in the Feb. 19, 2014 MIT News Office article by Larry Hardesty titled "MIT professor ‘made much of our world possible’ - Computing luminaries celebrate the work of MIT adjunct professor and Turing Award winner Butler Lampson, one of the fathers of the modern PC.," also posted below in its entirety.

Butler Lampson, an adjunct professor at MIT since 1987 and a technical fellow at Microsoft Research, has as good a claim as anyone to the title of “father of the modern PC.” As one of the founders of Xerox’s Palo Alto Research Center (PARC), Lampson helped create the Alto, the first computer to feature a mouse and a graphical user interface (GUI) — the progenitor of both the Apple Macintosh and the Windows operating system. He also led the development of Bravo, the first “what you see is what you get” — or WYSIWYG — word processor, which ran on the Alto.

Lampson turned 70 in December; last week, a group of computer science luminaries gathered at Microsoft Research New England, at the edge of the MIT campus, for a daylong conference celebrating his achievements. On hand were seven winners of the Turing Award, often called the Nobel Prize in computing. Two were PARC alumni, four were MIT professors, and the seventh was Lampson himself, who falls into both categories.

The talks were divided into three segments. In the first, Lampson’s PARC colleagues reminisced about their glory days. Two of the speakers were Turing winners: Charles Thacker, who led the design of the Alto’s hardware, and Alan Kay, who wrote the first full-fledged object-oriented programming language, smalltalk, a progenitor of modern languages like Java and Python. Two more played major roles in building billion-dollar businesses: Charles Simonyi, who worked with Lampson on Bravo and later led the development of Microsoft’s Office suite of applications, and Bob Metcalfe, whose company, 3Com, grew out of PARC research and was acquired by Hewlett-Packard for $2.7 billion in 2009.

Ubiquitous at PARC

Two major themes emerged from the morning sessions. The first was the sheer range of Lampson’s technical innovation. Lampson is known for having written the first draft of the Alto’s GUI operating system and leading its further development, but Thacker catalogued his contributions to the Alto’s hardware design. Simonyi described how Bravo was largely an elaboration of a three-page memo that Lampson drew up in the spring of 1974.

Metcalfe is often described as the inventor of Ethernet, the world’s most popular local-area networking technology and, arguably, the basis of Wi-Fi. But as he pointed out, he’s one of four people on the Ethernet patent, the others being Thacker, Lampson, and their PARC colleague David Boggs. Metcalfe’s company 3Com licensed the Ethernet patent because, as he explained, IBM was the subject of an antitrust suit at the time, and Xerox felt that, to avoid a similar liability, it had to involve a standards body in the commercialization of the technology. “Xerox decided that, to participate in making Ethernet a standard, it needed to license the patents for a nominal $1,000, which my company promptly paid,” Metcalfe said.

As the story of PARC is typically told, Xerox invented modern computing in the early 1970s but failed to capitalize on it — its neglect of Ethernet being a case in point. But in fact, another PARC invention, the laser printer, more than paid for the lab’s entire research budget, and a commercial Ethernet was the only way to move enough data to make the laser printer viable. As another PARC veteran, Bob Sproull, attested, the laser printer also has Lampson’s fingerprints on it. Sproull explained how Lampson helped develop the control system and character generator for the first Xerox laser printer, the 9700.

Strong opinions

The other theme of the morning sessions was just how formidable — and, as Metcalfe put it, “fast” — Lampson is in debate. Sproull mentioned a unit of measure used in computer science circles, which indicates the “speed of delivery of technical information” and is known as the lampson. “Most of us could ourselves only achieve millilampsons,” Sproull said.

Metcalfe concluded his talk with a list of seven lessons Lampson taught him. Some were technical: “Do the inner loops first.” Some were organizational: “Put the right person in for the right job.” But the last one, he said, was a principle he abides by: “I do not agree to change my mind just because you won the argument.”

“This I learned with Butler,” Metcalfe explained, “because Butler can win any argument, even when he’s wrong.”

Since coming to MIT, Lampson has been a member of the Cryptography and Information Security (CIS) Group, first at the Laboratory for Computer Science and, since 2003, in the Computer Science and Artificial Intelligence Laboratory; the second session dealt with his security work.

One of Lampson’s colleagues at CIS is his fellow Turing Award winner Ron Rivest, who helped develop the principles of public-key cryptography that protect almost all financial transactions on the Internet. (One of the other Turing winners in attendance was Silvio Micali, who together with a fourth CIS professor, Shafi Goldwasser, won the award last year.) Rivest described a system that he and Lampson developed that would enable the “democratization” of public-key cryptography, so that all Internet users could generate their own encryption “certificates.”

The system hasn’t been widely adopted, but Rivest expressed the hope that it still would be, as new reasons for concern about Internet security seem to appear almost weekly. Rounding out the session were talks by the Microsoft researchers Martin Abadi and Cynthia Dwork, who explained how Lampson had influenced and championed their own work on security.

Legacy

During the final session, a pair of young researchers took the floor, as a testament to Lampson’s enduring legacy. Microsoft researcher Adam Kalai described how Lampson had counseled him him on the design of a system that enables programmers to produce code simply by providing examples of inputs and outputs, while Nickolai Zeldovich, an associate professor of electrical engineering and computer science at MIT, explained how his work on enabling software applications to run on multicore computers drew on the principles he’d learned as an undergraduate in Lampson’s 6.826 (Principles of Computer Systems) class.

The final word on Lampson, however, came at the beginning of the day, in a statement from Eric Schmidt, Google’s former CEO and current executive chairman. “Butler is probably the broadest and smartest computer scientist today,” Schmidt said, in a statement read by Simonyi. “We all just tried to keep up with him — and almost always fell behind. His contributions made much of our world possible, and I am beyond grateful.”

Prof. Srini Devadas has developed new ways to manage caches for today's and tomorrow's massively multicore chips while improving performance efficiency. Devadas, EECS PhD student George Kurian and Omer Khan, an assistant professor of electrical and computer engineering at the University of Connecticut and a former postdoc in Devadas’ lab have reported this work in two papers.

Read more in the Feb. 19, 2014 MIT News Office article by Larry Hardesty titled "Smarter caching - Cleverer management of the local memory banks known as ‘caches’ could improve computer chips’ performance while reducing their energy consumption," also posted below in its entirety.

Computer chips keep getting faster because transistors keep getting smaller. But the chips themselves are as big as ever, so data moving around the chip, and between chips and main memory, has to travel just as far. As transistors get faster, the cost of moving data becomes, proportionally, a more severe limitation.

So far, chip designers have circumvented that limitation through the use of “caches” — small memory banks close to processors that store frequently used data. But the number of processors — or “cores” — per chip is also increasing, which makes cache management more difficult. Moreover, as cores proliferate, they have to share data more frequently, so the communication network connecting the cores becomes the site of more frequent logjams, as well.

In a pair of recent papers, researchers at MIT and the University of Connecticut have developed a set of new caching strategies for massively multicore chips that, in simulations, significantly improved chip performance while actually reducing energy consumption.

The first paper, presented at the most recent ACM/IEEE International Symposium on Computer Architecture, reported average gains of 15 percent in execution time and energy savings of 25 percent. The second paper, which describes a complementary set of caching strategies and will be presented at the IEEE International Symposium on High Performance Computer Architecture, reports gains of 6 percent and 13 percent, respectively.

The caches on multicore chips are typically arranged in a hierarchy. Each core has its own private cache, which may itself have several levels, while all the cores share the so-called last-level cache, or LLC.

Chips’ caching protocols usually adhere to the simple but surprisingly effective principle of “spatiotemporal locality.” Temporal locality means that if a core requests a particular piece of data, it will probably request it again. Spatial locality means that if a core requests a particular piece of data, it will probably request other data stored near it in main memory.

So every requested data item gets stored, along with those immediately adjacent to it, in the private cache. If it falls idle, it will eventually be squeezed out by more recently requested data, falling down through the hierarchy — from the private cache to the LLC to main memory — until it’s requested again.

Different strokes

There are cases in which the principle of spatiotemporal locality breaks down, however. “An application works on a few, let’s say, kilobytes or megabytes of data for a long period of time, and that’s the working set,” says George Kurian, a graduate student in MIT’s Department of Electrical Engineering and Computer Science and lead author on both papers. “One scenario where an application does not exhibit good spatiotemporal locality is where the working set exceeds the private-cache capacity.” In that case, Kurian explains, the chip could waste a lot of time cyclically swapping the same data between different levels of the cache hierarchy.

In the paper presented last year, Kurian; his advisor Srini Devadas, the Edwin Sibley Webster Professor of Electrical Engineering and Computer Science at MIT; and Omer Khan, an assistant professor of electrical and computer engineering at the University of Connecticut and a former postdoc in Devadas’ lab, presented a hardware design that mitigates that problem. When an application’s working set exceeds the private-cache capacity, the MIT researchers’ chip would simply split it up between the private cache and the LLC. Data stored in either place would stay put, no matter how recently it’s been requested, preventing a lot of fruitless swapping.

Conversely, if two cores working on the same data are constantly communicating in order to keep their cached copies consistent, the chip would store the shared data at a single location in the LLC. The cores would then take turns accessing the data, rather than clogging the network with updates.

The new paper examines the case where, to the contrary, two cores are working on the same data but communicating only infrequently. The LLC is usually treated as a single large memory bank: Data stored in it is stored only once. But physically, it’s distributed across the chip in discrete chunks. Kurian, Devadas, and Khan have developed a second circuit that can treat these chunks, in effect, as extensions of the private cache. If two cores are working on the same data, each will receive its own copy in a nearby chunk of the LLC, enabling much faster data access.

Sentry box

The systems presented in both papers require active monitoring of the chips’ operation — to determine, for instance, when working sets exceed some bound, or when multiple cores are accessing the same data. In each case, that monitoring requires a little extra circuitry, the equivalent of about 5 percent of the area of the LLC. But, Kurian argues, because transistors keep shrinking, and communication isn’t keeping up, chip space is not as crucial a concern as minimizing data transfer. Kurian, Devadas, and Khan are also currently working to combine the two monitoring circuits, so that a single chip could deploy the cache-management strategies reported in both papers.

“It is a great piece of work,” says Nikos Hardavellas, an assistant professor of electrical engineering and computer science at Northwestern University. “It definitely moves the state of the art forward.” Existing caching schemes, Hardavellas explains, do treat different types of data differently: They might, for instance, use different caching strategies for program instructions and file data. “But if you dig deeper into these categories, you see that the data can behave very differently. In the past, we didn’t know how to efficiently monitor the usefulness of the data. The [new] hardware design allows us to do this. That’s a significant part of the contribution.”

Moreover, Hardavellas says, “the two different designs seem to be working synergistically, which would indicate that the final result of combining the two would be better than the sum of the individual parts.” As for commercialization of the technology, “I see no fundamental reason why not to,” he says. “They seem implementable, they seem small enough, and they give us a significant benefit.”

The 2013-2014 Undergraduate Student Advisory Group in EECS (USAGE) is well into its third year. The group features over 30 undergraduate and graduate students who have committed to serving on this committee to provide feedback that will lead to enhancements in the EECS student experience. Specifically, USAGE members set out in the fall term with an agenda that included improvements to the advising experience in EECS and creating a meeting space that will be used by EECS students to meet informally.

USAGE was created in 2011-12 as part of the EECS department's strategic planning process. As a result of their input that year, the SuperUROP, a year-long advanced undergraduate research program, was launched the following year. USAGE team members thought about what they wanted to see in their department, polled their peers, and developed a program that addressed their desire for developing enhanced research skills.

USAGE students meet regularly with Prof. Chandrakasan, Prof. Albert Meyer (EECS Undergraduate Officer) and with Undergraduate Administrator Anne Hunter. Additionally, they meet with the Associate Department Heads - Professors David Perreault and Bill Freeman and other members of the department leadership.

Meet the USAGE members, whose brief bios and brief statements appear below.

Ali S. Al Shehab As senior in EECS, I am a 6.02 Lab Assistant and have enjoyed being House manager for Kappa Sigma, doing a summer UROP at the Mediated Matter- Media Lab working on robotic functions and at CSAIL where I wored on robotic arm function. Also, I have worked as a 'dynaMIT Mentor helping in science programs fro middle school kids and being a member of the MIT Chess, club, the MIT Arabic Students Assoc. and the MIT Muslim Students Assoc.  I would like to share my experiences and learn from others. And then use that knowledge to help other students. MIT has given me a lot and it is time to me to give something back. I am especially interested in working with and representing course 6 Meng students.
Sami Alsheikh I am a sophomore from Pensacola, Florida studying computer science. Although I am declared 6-3, I enjoy a lot of different subjects and want to be sure to use computer science in an interdisciplinary setting. Last summer, I interned at the Institute for Human and Machine Cognition, competing in the DARPA Robotics Competition. As a new member of USAGE, I hope to encourage the EECS department to push students to realize the true versatility of EECS while giving them the mindset to take advantage of this versatility.
Ishwarya Ananthabhotla My name is Ishwarya Ananthabhotla, and I’m presently a junior in Course 6-2.  I’m from Long Island, New York, and spent this past summer developing computational electromagnetics and signature reduction software for Boeing Defense in Saint Louis.  To build upon my interest in projects that span the intersection of mechanical design and EECS topics, I will be working as SuperUROP on the CSAIL Printable Robotics project, under Prof. Daniela Rus.  In the past, I’ve also had the opportunity to work on educational technology projects for the Media Lab’s Lifelong Kindergarten Group and MIT’s iLabs.  My goal as part of USAGE this year is to help improve the freshman experience and transition into the Course 6 family.
Kathryn W. Bartel I am a sophomore in course 6-2 with a minor in music. I love computer science in the context of art, music, and interactive technology. I'm the Membership Director at WMBR, MIT's radio station, and a founding member of MIT's Engineering Design Group for Exhibition. I'm currently doing research with the Computational Fabrication Group at CSAIL.  I am looking forward to improving the EECS department by participating in USAGE.
Jonathan Birjiniuk My name is Jonathan Birjiniuk and I am a junior in 6-1 from Massachusetts. During my time at MIT, research has played a significant role in my education. For the past two years I have been UROPing in the Computational Biophysics Group, where I research protein structure modeling and computation. I am also a member of the EECScon programming committee (the course 6 undergraduate research conference). As a member of USAGE, I would like to provide input to the department regarding undergraduate education as well as maintain and improve the great research opportunities provided within the department.
Stephan Boyer I grew up in the Bay Area, where I fell in love with computer science even before I knew about MIT.  When not doing computer science, I'm often making music, thinking about startups, or tutoring other students.  In the past I was interested in robotics and computer graphics, but these days I mostly think about type theory, math, and machine learning.  In addition to participating in several UROPS, I've spent over a year's worth of workdays interning at tech companies, and my perspective on academia vs. industry is one of the things I hope to bring to USAGE. My goal is to ensure that students get an accurate picture of what EECS is all about in introductory courses and to help students form a sense of how to pick good UROPs.  The EECS department has presented me with countless opportunities, and choosing which ones to embrace is a skill that took me years to develop.  I want to make sure that new EECS students know what resources are available to them, including both research opportunities and preparation for industry, and how to use them effectively.
Cody Coleman I graduated in June 2013 and am working on my Meng with MITx. My hometown is Winslow, NJ. During my time at MIT, I was a part of the Cambridge-MIT Exchange program, Eta Kappa Nu (HKN), and the Gordon Engineering Leadership (GEL) program. I also did a number of programs through MISTI including MIT Global Startup Labs. Outside of MIT, I have had two internships at Google.  Once I finish my MEng, I plan on trying to start my own company. As a USAGEW member, I hope to bring the needs of the department and the students together.
Michaela Ennis I’m a course 6-2 sophomore from New Jersey. My primary interest is artificial intelligence- I am currently doing a UROP in the Learning and Intelligent Systems Group at CSAIL. I was very involved with developing my high school’s research program, and I would like to continue this type of work during my time at MIT. Specifically, I would like to explore potential overlap of course 6 with course 9 (Brain and Cognitive Sciences).
Bruno Faviero My name is Bruno, and I am a junior in Computer Science. I'm heavily involved with entrepreneurship around campus as the Director of StartLabs and as a team member on the local Dorm Room Fund investment team. I like working on software projects and helping people start companies.  As a member of USAGE, I think my personal contribution will be providing an entrepreneurial angle and frame of mind to issues that arise and as the curriculum and other opportunities for students get developed.
Megan Gebhard My name is Megan Gebhard and I am a freshman from Michigan planning to major in Computer Science (6-3).  Here at MIT, I am a SWE department of liaison representative and play varsity volleyball. I am eager to gain experience in computer science at MIT and at my internship with Google next summer. I am very passionate about Course 6, and as a member of USAGE I would love to tell freshmen about the opportunities within the EECS department.
Ameesh K. Goyal I'm Ameesh, a 6-3 senior from Dallas, Texas. At MIT, I've been involved in a great UROP with the Network and Mobile Systems group for two years now, and I've done a number of internships in the industry. Currently, I have a growing interest in financial markets, but I have nothing planned for when I graduate. Through USAGE, I hope to contribute to any curriculum changes the department is planning and enhance the entrepreneurial experience for EECS students.
Ankush Gupta I am a 6-2 sophomore from Louisville, Kentucky and I'm really interested in making a positive impact to the world through computer science. I'm heavily involved with TechX at MIT, and have been working at Quizlet.com since last January.
Gustavo Goretkin I am a first-year M.Eng./Ph.D. student in the Learning and Intelligent Systems group at MIT. This is my third-year serving on USAGE. This year I am interested in working with the department and other students to determine ways in which the department can improve the gender disparity in EECS at MIT.
Jesika Haria I'm a Course 6-2 senior from Mumbai, India, and am passionate about leveraging technology to tackle real world challenges. I have worked at the Media Lab on information dissemination in low-tech social networks and with LIDS on comparison-based ranking for conference management systems. My present work is on DataHub, a Github-like hosted platform for organizing,sharing, and collaborating on data. My internships include Facebook and Securigin, an iOS security startup. I'm a UTA for 6.UAR, and a HKN tutor. I've always been interested in student life at MIT, and currently serve as co-President of ACM/ IEEE.  As a member of USAGE 2013-14, I hope to be able to facilitate social and professional interactions within students in the department, impact undergraduate advising, and ultimately to help foster an open, nurturing environment that enables my peers to make the most of their EECS experience at MIT.
Bianca Homberg I'm a junior in courses 6-2 and 18.  I am currently a UROP in the Distributed Robotics Lab working on the M-Blocks modular robots.  Here at MIT, I've been involved with the Educational Studies Program, both teaching classes and organizing behind the scenes.  Through my dorm and through HKN, I'm working on running technical interview panels to help underclassmen start the interview process more prepared. As a member of USAGE, I am interested in curriculum development and I am serving on the subcommittee for women in course 6.
Lars Johnson I am a junior from Minnesota majoring in 6-2 and 18 who plays the oboe and enjoys spending time outdoors. Since coming to MIT, I've had a UROP with music21, a python toolkit for computer-aided musicology, published and presented a paper about it at a Digital Humanities conference in Germany, received department recognition for my work as a teaching assistant for 6.01, and enjoyed summer internships at Thomson Reuters and Google. I am currently working on linear elasticity simulations with CSAIL's Computer Graphics Group and am serving as my dorm's technology chair. I'm interested in taking a more active role in shaping the department's future, particularly in the area of curriculum development.
Rishabh Kabra I am a senior studying computer science. I grew up in Dubai, U.A.E., and came to MIT with no doubts about what I wanted to major in. In my time here, I've been involved in research at both CSAIL and the Media Lab. I've participated in EECS teaching efforts as an LA and grader for many terms. I've also written reviews of classes for the HKN Underground Guide and am presently one of the chairs responsible for publishing it. I want to bring my experiences in the department to USAGE particularly to explore new curriculum offerings, increased entrepreneurial mentorship, and new campus facilities for students.
Ciara L. Kamahele-Sanfratello I am a Junior in course 6-3 from San Diego, California. I worked at Google in Zurich and Sydney this summer on a research project to help virtualize the distributed cluster management system. This semester, I have been UROPing with the Learning and Intelligent Systems group in CSAIL. I understand how hard it can be to enter the world of computer science without prior experience, and I want to help the department make the right decisions for students who are new to the field.
Keertan R. Kini I am a Sophomore in 6-2, and I have a wide variety of interests both in and out of Course 6. I have previously interned at Akamai Technologies, and I am currently helping develop MIT App Inventor. I would like to help ensure that Course 6 remains a community of opportunity and possibility for its members. More pragmatically, I wish to see it appropriately scale the quality of its offerings to its increasingly large student base. I would most like to give back to the department which has given me much already.
Jason Leung My name is Jason Leung and I am a current Sophomore majoring in 6-3 and 15. I grew up in New Zealand and my initial exposure to computer science at MIT has been a mind-opening experience. In various UROPs in my freshmen year, I have assisted postgraduates in both CSAIL and Sloan. I intend to do many of the course 6 headers and AUS subjects this year and believe I can provide strong feedback on these classes. Through USAGE, I would like to increase the number of networking events that allow employers to connect with EECS undergraduates. At MIT I am a board member of SBC, do.it@MIT and MITPokerClub - all of which offer amazing networking opportunities. I hope I can become part of this amazing opportunity to assist other course 6 students both with internal and external opportunities.
WeiHua James Li I am Wei Li and I am a senior majoring in Computer Science and Economics. I was born and raised in China and spent about three years in New York City for high school. I love coding, investing, and any ideas that aim to combine these two together. I am working on building the next generation platform that focuses on collecting and applying personal data to improve daily experience, especially in the area of on-campus teaching and learning. The ultimate goal of this platform is to transform how we live, work, and think through data. As a remember of USAGE, I want to bridge any gap between the students and the department, improve course six experience, and help to define the direction that the department heads for the coming year.
Lao Manting I am currently a sophomore studying 6-2 with a wide variety of interests in Course 6. As a freshman at MIT, I did UROPs in Course 12 and for the Systems Engineering Advancement Research Initiative. I am currently Publicity Chair for the MIT IEEE/ACM Club and helped to establish an international partnership between our branch and the JKU-Linz Branch in Austria this summer. My other hobbies include being fencing epee for the MIT Varsity Fencing Team, traveling, and playing piano. This is my first year on USAGE and I am very excited! I want to help make MIT EECS a more tight-knit community by facilitating student-faculty interactions and bringing new opportunities to Course 6 students.
Colin McDonnell I'm Colin, a sophomore in 6-2.  I'm a military brat, so I've lived all over the United States as well as in Germany, Turkey, and England.  I've worked at the Brookings Institution and at the National Bureau of Economic Research to pursue my passion for government and economics, although now I'm shifting focus to entrepreneurship, especially product design and energy.  After a year and a bit at MIT, I still don't know much, but I do have ideas about how to foster a better sense of Course 6 community.
Manushaqe Muco I am a 6.3 senior. I come from Vlora, Albania. My research experience has quite some breadth; I've done work in network coding, machine learning, genetic programming, software engineering, and also a bit of hardware engineering. For the past two years, my focus has been the field of Artificial Intelligence (AI), and I am currently working with the Genesis group at MIT on a story understanding system.// My research experience comes mostly from UROPs and MISTI.  I consider undergraduate research to be a great opportunity, both challenging and rewarding. It is because of trying different UROPs, that I was able to build my background and decide on focusing myu future career in AI. I want to help facilitate the journey of MIT students through Course 6. I also want to help bring new ideas for getting and keeping students motivated, as well as giving them the necessary skills to succeed during and after MIT.
Pratheek B. Nagaraj I am a sophomore in course 6-2 originally from South Florida. Previous to my MIT experience I was involved in research in my high school. Now here at MIT, I continue my research endeavors working on an interdisciplinary computer science and genetics project as well as in CSAIL. I have also held internships with NASA and Amazon. As a member of USAGE, I hope to bolster the undergraduate research environment in Course 6 as well as improve the curriculum and assistance provided to students.
Santhosh Narayan Hey! My name is Santhosh Narayan, and I'm a junior at MIT. Hailing from The Region, I'm an avid Chicago sports fan and love to play sports in my free time. I decided to major in computer science because I'm interested in how big data is going to change the daily life of my generation.//On campus, I'm a Co-Founder of do.it@MIT and a Co-Director of the Consulting Focus Group within Sloan Business Club. I'm also a board member of Asian American Association and the Course 6 Representative for PBE. Outside of MIT, I've studied abroad at the London School of Economics as a Fung Scholar, and my internship experiences include Morgan Stanley, Bain & Company, System Two Advisors, Fairhaven Capital Partners, and Fidelity Investments. Upon graduation, though, I hope to start a venture of my own. As a member of USAGE, I hope to help communicate student input into decisions regarding the future of EECS to enhance student experiences both here at MIT and beyond.
Henry Nassif My name is Henry Nassif and I am a junior in Electrical Engineering and Computer Science. I have previously worked at eBay doing backend integration and NASA designing algorithms for controlling satellites. I have also done research in human-computer interaction at the Media Lab and at Stanford University. When I finish my undergraduate degree, I plan on pursuing a Master of engineering in Artificial Intelligence and then starting my own company.   Through USAGE, I hope to help foster entrepreneurship among EECS students and contribute in shaping the future of the EECS department.
Anvisha Pai My name is Anvisha Pai and I'm a Senior in 6-2 from Mumbai, India - and this is my second year on USAGE. I am also a SuperUROP this year, working with Prof. Rob Miller on personalized informal learning. I spent the last summer at Google, working on a new feature for Street View, and the summer before that at Boeing. On campus, I am the co-president of the South Asian Association of Students and have been involved in Techfair and the Sloan Business Club.
Victor Pontis Hi, my name is Victor Pontis and I am majoring in Computer Science and Physics. I am from San Diego and picked up EECS in high school through an autonomous robotics competition.  My interest in computer science gained steam during freshman IAP where I taught myself web-dev with two close friends and developed a study tool called Termstile. Since then I have done internships at Kyruus, CardSpring and Palantir. Through USAGE I want to encourage student collaboration and help foster a community in the department. I also want to emphasize entrepreneurship through class projects and workshops.
Aakanksha Sarda I'm a Junior in course 6-2 from Mumbai, India. My interest in everything visual has come a long way since my freshman UROP building 3D TVs - I'm now on the Tech's video staff and working on de-blurring JPEG images for my SuperUROP. As an EECS senior I am one of two undergraduate teaching assistants for the SuperUROP 2013 Fall term class 6.UAR. I spent my summers at Facebook and Dropbox, taking new features from conceptualization to launch, for products that I use and love. Course 6 has really shaped and defined every aspect of my MIT experience, and now I'm very excited about the opportunity to give back to the EECS student community as part of USAGE!
Isra Shabir I am a senior in 6-3 from Al Ain, United Arab Emirates interested in the intersection of technology with arts, music and everything that adds color to life. My introduction to Computer Science is very much different from my peers in that I switched to 6-3 from Bioengineering in my junior year without having any coding experience. While, I'm relatively new to the field, I've tried to immerse myself in cool technologies both in and outside of class. There's a long way to go but I am confident I've found my interests. In the past, I've done internships and also tried to assist with a family startup. I've also UROPed within various groups at MIT. Through my varied experiences in & outside of MIT, I wish to bring a new perspective on how to approach & dive into this field and also work on making administrative decisions that improve the experience of a course 6 student.
Tal Tchwella I am out of the box thinker, avid learner and a technology enthusiast. I am currently a senior and MEng student majoring in Computer Science, and I absolutely love and enjoy the unparalleled opportunities I had been given here! Originally from Israel, before MIT, I served in the Israeli Defense Forces as an Intelligence officer. During my time at MIT, I participated on various research projects, worked in startups and interned during the summers in IBM and Microsoft as a product manager. I hope to help create better opportunities than those I had available to make others’ time in course 6 much more enjoyable.
Prathiksha R. Thaker I am out of the box thinker, avid learner and a technology enthusiast. I am currently a senior and MEng student majoring in Computer Science, and I absolutely love and enjoy the unparalleled opportunities I had been given here! Originally from Israel, before MIT, I served in the Israeli Defense Forces as an Intelligence officer. During my time at MIT, I participated on various research projects, worked in startups and interned during the summers in IBM and Microsoft as a product manager. I hope to help create better opportunities than those I had available to make others’ time in course 6 much more enjoyable.
Srinidhi Viswanathan Hi, I’m a sophomore majoring in Course 6-3, from Portland, Oregon. I spent my freshman year working at the MIT Media Lab in the Information Ecology group, implementing code-level event tracking to better adapt mapping software for public needs, and spent last summer as a software engineering intern at Intel Corporation. As a member of USAGE, I look forward to facilitating the journey through Course 6 for MIT students. I think we can really strengthen the student-faculty relations and ultimately connect with EECS alumni who have recently entered the workforce and are willing to share their firsthand experiences with undergraduates.
Benjamin X. Xie Hey there! Call me Benji. I am a junior majoring in computer science (6-3), concentrating in education. People are awesome. And so is technology! That's why I'm all about developing technology for humans. My current work involves leveraging data to understand how people learn programming and how to improve that experience. Away from the bits and bytes, I am leading MIT's Cross Country Team, planning EECScon 2014, and finding my shanti in yoga! I see USAGE as part of a two-way conversation. I want to listen to both students and administration alike, and work towards an EECS department that is student-oriented and a student body that is collaborative and engaged!
David Ye I'm currently a junior in 6-2, and I'm originally from Little Rock, AR. I've been involved in robotics research through the Personal Robots Group in the Media Lab, and am currently part of the Learning and Intelligent Systems Group in CSAIL. I've also been involved in the solar car team since freshman year, and interned at VMware this past summer. I've found that many of my closest and most valuable connections at MIT have been made by working with peers on interesting and challenging problems, and I hope to create more opportunities for Course 6 students to do the same by encouraging collaboration and project-based learning.

Award named in honor of Prof. Jonathan Allen, sixth director of the Research Laboratory of Electronics, for his dedication to mentoring and developing junior faculty members.

Professor Yoel Fink, Director of The Research Laboratory of Electronics (RLE) at the Massachusetts Institute of Technology (MIT), designated Vivienne Sze, Assistant Professor of Electrical Engineering, as the 2013 recipient of The Jonathan Allen Junior Faculty Award.  [See the Dec. 16, 2013 RLE Announcement.]

The award is named in honor of Professor Jonathan Allen, sixth director of the Research Laboratory of Electronics, for his dedication to mentoring and developing junior faculty members.

Professor Sze joined the Electrical Engineering and Computer Science Department as an assistant professor in August 2013. She received her B.A.Sc. degree in Electrical Engineering from the University of Toronto in 2004, and her S.M. and Ph.D. degrees in Electrical Engineering and Computer Science from MIT in 2006 and 2010, respectively. From September 2010 to July 2013, Professor Sze was a Member of Technical Staff in the Systems and Applications R&D Center at Texas Instruments.

Professor Sze's group in RLE focuses on development and implementation of energy-efficient and high-performance systems for various multimedia applications such as video coding/processing, imaging and vision. Her work on implementation-friendly video compression algorithms was used in the development of the latest video coding standard HEVC/H.265, enabling it to deliver better compression than previous standards, while still achieving high processing speeds and low hardware cost. She aims to develop energy-aware algorithms and efficient architectures for various energy-constrained applications including portable multimedia, health monitoring and distributed sensing.

She has received various awards including the Jin-Au Kong Outstanding Doctoral Thesis Prize in 2011, the 2007 DAC/ISSCC Student Design Contest Award, the 2008 A-SSCC Outstanding Design Award, the Natural Sciences and Engineering Research Council of Canada (NSERC) Julie Payette fellowship in 2004, the NSERC Postgraduate Scholarships in 2005 and 2007, and the Texas Instruments Graduate Woman's Fellowship for Leadership in Microelectronics in 2008. In 2012, she was selected by IEEE-USA as one of the "New Faces of Engineering." Additionally, EECS Department Head Anantha Chandrakasan announced the appointment of Vivienne Sze as the Emanuel E. Landsman (1958) Career Development Assistant Professor in October 2013.

Professor Yoel Fink, Director of RLE and Professor of Materials Science, said, "I am thrilled to have a junior faculty researcher of Vivienne's caliber in RLE and honored to have this opportunity to provide her the financial support afforded by the Jonathan Allen Award at such an important point in her career. Vivienne's research in compression and coding algorithms has the potential to provide ground breaking developments throughout a broad spectrum of applications and revolutionize the way data is encoded."

Armando Solar-Lezama, associate professor in the Electrical Engineering and Computer Science Department at MIT and principal investigator in the Computer Science and Artificial Intelligence Lab has developed an improved method to correct code using the programming language called Sketch. Solar-Lezama and his graduate students Rohit Singh, Rishabh Singh, and Zhilei Zu, along with MIT senior Rebecca Krosnick will present their work (Modular Synthesis of Sketches using Models) at the 2014 Verification, Model Checking, and Abstract Interpretation Conference.
Read more in the Feb. 25, 2014 MIT News Office article by Larry Hardesty titled "Self-completing programs - A system that automatically fills in the gaps in programmers’ code becomes more powerful.," also posted below.

Since he was a graduate student, Armando Solar-Lezama, an associate professor in MIT’s Department of Electrical Engineering and Computer Science, has been working on a programming language called Sketch, which allows programmers to simply omit some of the computational details of their code. Sketch then automatically fills in the gaps.
If it’s fleshed out and made more user-friendly, Sketch could ultimately make life easier for software developers. But in the meantime, it’s proving its worth as the basis for other tools that exploit the mechanics of “program synthesis,” or automatic program generation. Recent projects at MIT’s Computer Science and Artificial Intelligence Laboratory that have built on Sketch include a system for automatically grading programming assignments for computer science classes, a system that converts hand-drawn diagrams into code, and a system that produces SQL database queries from code written in Java.
At this year’s Verification, Model Checking, and Abstract Interpretation Conference, Solar-Lezama and a group of his students — grad students Rohit Singh, Rishabh Singh, and Zhilei Zu, along with MIT senior Rebecca Krosnick — described a new elaboration on Sketch that, in many cases, enables it to handle complex synthesis tasks much more efficiently. The researchers tested the new version of Sketch on several existing applications, including the automated grading system. In cases where the previous version would “time out,” or take so long to reach a solution that it simply gave up, the new version was able to correct students’ code in milliseconds.
Sketch treats program synthesis as a search problem. The idea is to evaluate a huge range of possible variations on the same basic program and find one that meets criteria specified by the programmer. If the program being evaluated is too complex, the search space balloons to a prohibitively large size. In their new paper, the researchers find a way to shrink that search space.
Chain of command
“When you’re trying to synthesize a larger piece of code, you’re relying on other functions, other subparts of the code,” Rishabh Singh explains. “If it just so happens that your system only depends on certain properties of the subparts, you should be able to express that somehow in a high-level language. Once you are able to specify that only certain properties are required, then you are able to successfully synthesize the larger code.”
For instance, Singh explains, suppose that one of the subparts of the code is a routine for finding the square root of a number, and a higher-level function relies on the results of that computation. If the previous version of Sketch were trying to evaluate variations of the high-level function, for each variation, it would also have to evaluate variations of the square-root function. Since finding square roots is a complex process, that would make the search prohibitively time-consuming.
With the new version of Sketch, however, the programmer can simply specify conditions that the square-root function has to meet: The output multiplied by itself must equal the input. Now, Sketch can satisfy itself that the square-root function it comes up with meets that criterion and move on to the higher-level function. It doesn’t need to re-evaluate the square-root function at every pass.
In fact, this places a slightly greater onus on the programmer, who now has to reason about the criteria that each low-level function must meet. But it allows Sketch to handle much more complicated problems.
Immediate prospects
Solar-Lezama concedes that it will take a good deal of work before Sketch is useful to commercial software developers. “The application as a tool-building infrastructure, using it to build higher-level systems on top of it, we’ve demonstrated very convincingly by building a variety of systems that do things that couldn’t be done before,” he says.
He has, however, conducted usability studies with Sketch, recruiting MIT undergraduates with only a semester’s worth of programming experience to test it. In all cases, he says, the students successfully used Sketch to produce working code. But in many cases, the missing code took an unacceptably long time to synthesize, because of the way the students had described the problem.
“It still requires a level of expertise and understanding about the underlying technology in order for it not to blow up,” Solar-Lezama says. “As far as the more ambitious goal of everybody dumping C and using Sketch instead, we’d still have to push quite a bit.”
As Rajeev Alur, a professor in the Department of Computer and Information Science at the University of Pennsylvania, explains, the new paper draws on principles from the field of “formal verification,” which, Alur says, investigates methods for “checking the correctness of programs using automated reasoning.”
“In verification, people have always used modular reasoning as a technique to make it scale to more interesting systems,” Alur says. “What this paper does is take some of those ideas and meshes them nicely with the synthesis routines they have in Sketch.”
Alur acknowledges that “having a general software developer use [Sketch], maybe that’s not realistic in the foreseeable time.” But, he says, “even now it could be used in very specific, specialized tasks. If you’re trying to optimize some piece of code for some reason, instead of doing all that fine-tuning of the code manually, now a system like Sketch could do it.”

Sangeeta Bhatia, the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science, has teamed with current and former postdocs and a graduate student to develop a simple, quick and cheap test to improve cancer diagnosis rates. The test, much like that used for pregnancy, reveals within minutes the presence of cancer cells in urine. This new test will be particularly helpful in developing countries where the typical medical infrastructure -- but also be useful in the U.S.

Read more in the Feb. 25, 2014 MIT News Office article by Anne Trafton titled "A paper diagnostic for cancer - Low-cost urine test developed by MIT engineers amplifies signals from growing tumors to detect disease," also posted below. [Photo: MIT professor Sangeeta Bhatia has developed a new paper diagnostic that can detect cancer by identifying biomarkers in the patient's urine. Photo credit: Bryce Vickmark, MIT News Office]

Cancer rates in developing nations have climbed sharply in recent years, and now account for 70 percent of cancer mortality worldwide. Early detection has been proven to improve outcomes, but screening approaches such as mammograms and colonoscopy, used in the developed world, are too costly to be implemented in settings with little medical infrastructure.

To address this gap, MIT engineers have developed a simple, cheap, paper test that could improve diagnosis rates and help people get treated earlier. The diagnostic, which works much like a pregnancy test, could reveal within minutes, based on a urine sample, whether a person has cancer. This approach has helped detect infectious diseases, and the new technology allows noncommunicable diseases to be detected using the same strategy.

The technology, developed by MIT professor and Howard Hughes Medical Institute investigator Sangeeta Bhatia, relies on nanoparticles that interact with tumor proteins called proteases, each of which can trigger release of hundreds of biomarkers that are then easily detectable in a patient’s urine.

“When we invented this new class of synthetic biomarker, we used a highly specialized instrument to do the analysis,” says Bhatia, the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science. “For the developing world, we thought it would be exciting to adapt it instead to a paper test that could be performed on unprocessed samples in a rural setting, without the need for any specialized equipment. The simple readout could even be transmitted to a remote caregiver by a picture on a mobile phone.”

Bhatia, who is also a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science, is the senior author of a paper describing the particles in the Proceedings of the National Academy of Sciences the week of Feb. 24. The paper’s lead authors are graduate student Andrew Warren, postdoc Gabriel Kwong, and former postdoc David Wood.

Amplifying cancer signals

In 2012, Bhatia and colleagues introduced the concept of a synthetic biomarker technology to amplify signals from tumor proteins that would be hard to detect on their own. These proteins, known as matrix metalloproteinases (MMPs), help cancer cells escape their original locations by cutting through proteins of the extracellular matrix, which normally holds cells in place.

[Photo: The paper test strips, which work similar to a pregnancy test, reveal the presence of proteins associated with cancer. They can also be designed to detect other diseases. Photo credit: Bryce Vickmark]

The MIT nanoparticles are coated with peptides (short protein fragments) targeted by different MMPs. These particles congregate at tumor sites, where MMPs cleave hundreds of peptides, which accumulate in the kidneys and are excreted in the urine.

In the original version of the technology, these peptides were detected using an instrument called a mass spectrometer, which analyzes the molecular makeup of a sample. However, these instruments are not readily available in the developing world, so the researchers adapted the particles so they could be analyzed on paper, using an approach known as a lateral flow assay — the same technology used in pregnancy tests.

To create the test strips, the researchers first coated nitrocellulose paper with antibodies that can capture the peptides. Once the peptides are captured, they flow along the strip and are exposed to several invisible test lines made of other antibodies specific to different tags attached to the peptides. If one of these lines becomes visible, it means the target peptide is present in the sample. The technology can also easily be modified to detect multiple types of peptides released by different types or stages of disease.

“This is a clever and inspired technology to develop new exogenous compounds that can detect clinical conditions with aberrantly high protease concentrations,” says Samuel Sia, an associate professor of biological engineering at Columbia University who was not involved in the research. “Extending this technology to detection by strip tests is a big leap forward in bringing its use to outpatient clinics and decentralized health settings.”

In tests in mice, the researchers were able to accurately identify colon tumors, as well as blood clots. Bhatia says these tests represent the first step toward a diagnostic device that could someday be useful in human patients.

“This is a new idea — to create an excreted biomarker instead of relying on what the body gives you,” she says. “To prove this approach is really going to be a useful diagnostic, the next step is to test it in patient populations.”

Developing diagnostics

To help make that happen, the research team recently won a grant from MIT’s Deshpande Center for Technological Innovation to develop a business plan for a startup that could work on commercializing the technology and performing clinical trials.

Bhatia says the technology would likely first be applied to high-risk populations, such as people who have had cancer previously, or had a family member with the disease. Eventually, she would like to see it used for early detection throughout developing nations.

Such technology might also prove useful in the United States, and other countries where more advanced diagnostics are available, as a simple and inexpensive alternative to imaging. “I think it would be great to bring it back to this setting, where point-of-care, image-free cancer detection, whether it’s in your home or in a pharmacy clinic, could really be transformative,” Bhatia says.

With the current version of the technology, patients would first receive an injection of the nanoparticles, then urinate onto the paper test strip. To make the process more convenient, the researchers are now working on a nanoparticle formulation that could be implanted under the skin for longer-term monitoring.

The team is also working to identify signatures of MMPs that could be exploited as biomarkers for other types of cancer, as well as for tumors that have metastasized.

The research was funded by a National Science Foundation Graduate Research Fellowship, a Mazumdar-Shaw International Oncology Fellowship, the Ruth L. Kirschstein National Research Service Award from the National Institutes of Health, the Burroughs Wellcome Fund, the National Cancer Institute, and the Howard Hughes Medical Institute.

Written by Patricia Sampson

Photos by Rahul Rithe

Start6, the new EECS IAP workshop for immersion in innovation and entrepreneurship, wrapped up its third week with sendoffs from two icons in the world of startups: Drew Houston, ’05, Co-founder and CEO of Dropbox, and Institute Professor Bob Langer.

Houston joined Anantha Chandrakasan, EECS Department Head and creator of Start6, for a fireside chat on Monday, January 27. A full crowd of interested students from across campus came to hear Houston describe his experiences and offer advice on taking the plunge to launch a startup.

More software-run startups mean more CS-educated and technically savvy CEOs

Pointing out how enrollment in EECS and particularly in Computer Science is up almost 30%, Chandrakasan queried Houston about the place of CS in the overall MIT curriculum. “Should computing be a general Institute requirement, like Chemistry or Physics, for example?” Chandrakasan asked.

Houston not only agreed that CS should be an Institute requirement, but made the case for this change. He pointed out that over the last 15 years, the Internet has completely changed how people find information and how they act and use commerce – giving as an example the widespread use of credit cards online. “Now all kinds of major industries including education and agriculture are being turned upside-down by software, which is rocking all industry,” Houston told the large crowd gathered in 34-101. “So absolutely, people are massively underestimating the shift. It’s now not only possible but it’s ordinary that a couple of kids in a dorm room can build something that reaches millions of people, completely changing the way [people] do something.”

As a student at MIT, Houston told the crowd, he not only loved 6.046, Intro to Algorithms, but he also discovered, while taking several management classes, that methodologies in the business world – including negotiation – were not magic, but followed an understandable framework. He suggested that picking up the business side on the fly was not out of reach for any MIT engineering student. “VCs are a lot happier if you’re wearing a brass rat from Course 6,” he noted, “than an MBA from Harvard.”

Chandrakasan asked Houston about the November 2013 Forbes article on Stanford versus MIT startups – a piece that suggested marketing-based startups out of Stanford trump technology-driven startups out of MIT.

Houston repeated that as more and more industries are software-driven, technology will be more and more important. “Although Stanford students are surrounded with startups everywhere in the Bay area,” Houston said, “think about Zuckerberg and Gates… engineers first and then picked up the business side. It’s not some other class of people that can only figure this [marketing and management] out,” Houston challenged the Start6 students.

Preparing MIT to lead the new wave of entrepreneurs

Houston also suggested that as MIT seeks to foster entrepreneurship, more students should be encouraged to take up to 6-month internships with top-tier, venture-backed startups. He was personally involved in five other startups before Dropbox.

Houston was also involved as an MIT undergraduate in leadership kinds of roles such as running fraternity rush and becoming active in an entrepreneurship club. He also credits training himself on management principles by poring over management textbooks he bought online.

“What got you up to speed to take on founding Dropbox?” one student asked.

Houston responded that the process took lots of “baby steps” from his first startup internship as a senior in high school to deciding to build Dropbox with Course 6 classmate and then junior, Arash Ferdowsi, to managing a company of over 500 employees. At the time he conceived of Dropbox — after forgetting his memory stick as he left Boston for NYC in late 2006, after he had graduated — Drew realized the beauty of MIT’s Athena workstations. A workstation was always available – when he was a student. His and Arash’s goal as they developed the code that became Dropbox was (and is) to become the Athena station for the world. “It felt delusional … to have this goal,” Drew said. “But that was when there were just two of us.”

Product- versus software-based startups: Bob Langer’s formula

While Drew Houston represents an entrepreneurial idol as a recent Course 6 graduate, as the speaker at the MIT Commencement (2013) and as a frequent mentor for EECS students engaged in innovation, Robert S. Langer, the David H. Koch Institute Professor, the most cited engineer in history, and founder of 26 companies, gave the final Start6 sendoff on January 28. He shared his formula with a receptive group.

Langer recommended starting with platform-building technologies for long-term successful manufacturing of products that are covered by a broad blocking patent, and established by publication in a top journal. He encouraged what he called the ‘champion effect.’ “You want people who will walk through walls to make things work to be at the company, ” he said. “You care a lot more for [their] passion than experience.” He cited Steve Job’s starting Apple, the company’s subsequent decline when Jobs was forced to leave, and its historic rise to the top on his return.

From the lab to creating companies – a less common concept in the 1970s

Langer told the stories of six companies that he founded with his students, starting in the late 1970s. He noted that in five of the six, the idea of starting a company followed the publication and broad patent of the original discovery. He said that although MIT was not actively encouraging startups in those days, his experiences were all successful. Not one of his companies has gone under.

As a postdoc in the 1970s under Dr. Judah Folkman at Boston Children’s Hospital, Bob Langer developed a way to deliver large molecules in unaltered state for slow-release therapeutic treatments. After 200 unsuccessful trials, he discovered a way to accomplish this and published the work in Nature. Although Children’s Hospital had never filed for a patent and the US Patent Office turned down his requests for five years, Langer was able to gather literature citations pointing to how surprising his results were, and the scientists who wrote them signed affadavits that this was true. The patent examiner was convinced by these statements, and a very broad patent was granted.

Several large companies licensed this patent but didn’t work very hard to develop them, Langer related. So with a group of former students, he started a company, which merged with the nascent company on the floor below. Today, Alkermes, a $7 billion company with 1200 employees, produces 25 products that treat schizophrenia, diabetes and other major human disorders.

After describing of five additional companies and answering a number of questions, Prof. Langer advised that the biggest reason for success or failure is the CEO. He also urged that younger inventors do due diligence to determine how to deal with venture capitalists and investors. “The pie is only so big. Dig deep in your heart about what you want to do.”

In answer to a question about Drew Houston’s lack of emphasis on patents, Bob Langer agreed with Houston’s advice, noting the importance of patents in the life sciences compared with the information and computer sciences where marketing takes a bigger role. From their own perspectives, Langer and Houston each encouraged the Start6 students. As Drew Houston put it, “Do it [launch a startup] now!”

Start6 concluded its final day (of twelve) with the last of the individual project presentations – all potential startups that will continue to benefit from further mentorship and development. Start6 students were also invited to sign up for a spring break trip to the Bay area to visit with several VCs and startups.

Charles E. Leiserson has been named recipient of the IEEE Computer Society's 2014 Taylor L. Booth Award for his contributions to computer science education.

Noted for coauthoring the textbook “Introduction to Algorithms,” one of computer science’s most cited publications, Prof. Leiserson is recognized by the IEEE Computer Society  “for worldwide computer science education impact through writing a best-selling algorithms textbook and developing courses on algorithms and parallel programming.”

A member of the MIT Department of Electrical Engineering and Computer Science faculty since 1981, Prof. Leiserson created undergraduate courses on algorithms and discrete mathematics as well as an undergraduate class on software performance engineering (6.172) which teaches parallel programming, one of several techniques aimed at writing fast code. In recognition of his contributions to undergraduate teaching, Leiserson was selected as a MacVicar Faculty Fellow in 2007, MIT’s highest recognition for undergraduate teaching. Prof. Leiserson has graduated over two dozen doctoral students and supervised more than 60 master’s and bachelor’s theses.

Since 2002, Prof. Leiserson has developed and led numerous workshops for faculty and students in understanding nontechnical human issues in technical teams in academia. These efforts include the annual workshop available to faculty worldwide known as Leadership Skills for Engineering and Science Faculty and the founding of MIT’s Undergraduate Practice Opportunities Program (UPOP). He was for many years the head of the computer-science program for the Singapore-MIT Alliance, one of the first distance-education collaborations, which produced popular video lectures of his undergraduate course on algorithms.

A principal investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL), Prof. Leiserson and his research group, The Supertech Research Group, investigates the technologies that support scalable high-performance computing including hardware, software and theory as related to engineering reality. A graduate of Carnegie Mellon (1981), Leiserson was recognized with the first ACM Doctoral Dissertation Award, as well as the Fannie and John Hertz Foundation’s Doctoral Thesis Award for his PhD thesis titled "Area-Efficient VLSI Computation".

Prof. Leiserson coauthored the first paper on systolic architectures, a specialized form of parallel computing and invented the retiming method of digital-circuit optimization. On leave from MIT at Thinking Machines Corporation, he designed and led the implementation of the network architecture for the Connection Machine Model CM-5 Supercomputer, which incorporated the fat-tree interconnection network he developed at MIT. He introduced the notion of cache-oblivious algorithms and developed the Cilk multithreaded programming technology. His development of several Cilk-based parallel chess-playing programs resulted in numerous prizes in international chess competitions. On leave from MIT as Director of System Architecture at Akamai Technologies, Prof. Leiserson led the engineering team that developed a worldwide content-distribution network numbering over 20,000 servers.

The Taylor L. Booth award will be presented to Prof. Leiserson in early June at the IEEE Computer Society’s Board of Governors meeting in Seattle.

Students build their own electronics with help from Cypress Semiconductor

Lauren J. Clark

Electrical engineering and computer science students at MIT are accustomed to designing the circuitry or control algorithms for, say, a robot. But they have largely been left out of building the robot itself. Now, a teaching laboratory called the Engineering Design Studio (EDS) enables them to fabricate entire electronics-based systems. [Open since January Independent Activities Period, the EDS will formally open April 1.]

“I had never soldered before I came [to MIT], I had never used a drill,” says Lizi George ’12 MEng’14, who worked as a teaching assistant in the new fabrication facility. “The majority of EECS students don’t have that experience. But that’s one of the goals of MIT—the ‘mind and hand’ motto, getting the hands-on experience.”

George had a revelation when, as an undergraduate, she took machining and power electronics classes with Steven Leeb ’87, an EECS professor and member of the Research Laboratory of Electronics. “I was totally struck—I had never built anything before,” she says.

Leeb lent his own laboratory space to undergraduates. But the equipment wasn’t up to date, and ongoing research projects took precedence over class assignments. He decided that MIT needed an advanced prototyping facility dedicated to EECS.

“If you think about MIT after World War II or during the sixties and seventies, that’s when the students who were coming to us fixed cars or were ham radio operators,” says Leeb, who earned his bachelor’s, master’s and PhD in EECS at MIT.

“The nature of how to connect engineering science with practical applications has changed. [With EDS], we want to convey some of the excitement of modern manufacturing.” With laser cutting tools, a soldering station and other fabrication equipment, Leeb says, “students can easily create all the mechanical assembly required for an iPod dock and two speakers. They learn first-hand how two resistors are going to lower a voltage. It’s not just an abstract problem.”

Brian Sennett ’13, an EECS graduate student and teaching assistant in EDS, says he knew in high school that he wanted to be an engineer. “When I came to MIT I was undecided between EECS and mechanical engineering,” he says. “I liked computers, so I gravitated to computer science. But I realized I’d rather do more hands-on building.” EDS enables students like him to experience “how electrical things work with mechanical things,” Sennett says. For his thesis, he is building a sensor system that will be able to detect whether and how many people are in a room based on their electrical properties.

The students in EDS are making use of a game-changing technology called PSoC, or programmable system on a chip. Provided by Cypress Semiconductor, which sponsored the creation of EDS in Building 38, the chips combine the capability to receive analog input—from human touch or a temperature sensor, for example—and process that input digitally for the desired application. Previously, these different capabilities required separate components, such as amplifiers, an analog-digital converter, and a computer.

[Photo right: Freshmen, including Winter Guerra, built loud-speakers and stereo-amplifiers of their own design in the new Cypress Engineering Design Studio to explore resonant systems and power conversion. (Photo credit: Steve Leeb)]

PSoC, says Leeb, “is like having a whole parts store on a chip. You can program it to be what you want.” Currently, these chips are in use in everything from smart phones to automobile control consoles to computer-network servers.

Cypress CEO T. J. Rodgers, who created the Cypress University Alliance in 2006 as a way to engage with engineering students and educators, says that his company’s alignment with MIT is strong.

“MIT students grasp what our design tools do for them, and we’re trying to enable them to be the great engineers that we know they’re going to be,” Rodgers says. “We believe in getting the best minds and enabl

What is the role of big data? How should individual rights be protected in the face of big data? Big Data's challenges were presented and discussed by speakers including John Podesta, White House Counselor, MIT President L. Rafael Reif, and Cynthia Dwork, a distinguished scientist at Microsoft Research and a pioneer of “differential privacy.” In two technical panel discussions, MIT EECS faculty including edX President Anant Agarwal, and Professors John Guttag, Manolis Kellis, Shaffi Goldwasser, Nickolai Zeldovich, and Vinod Vaikuntanathan provided perspective on big data's usefulness in medical research and fields requiring access to large data sets and on the alternatives for securing that data.

Read more in the March 5, 2014 MIT News Office article by Larry Hardesty titled, "MIT, White House co-sponsor workshop on big-data privacy - MIT hosts the first of three conferences on privacy policy," also posted below in its entirety. [Photo credit: Dominic Reuter/MIT News Office]

On Monday, MIT hosted a daylong workshop on big data and privacy, co-sponsored by the White House as part of a 90-day review of data privacy policy that President Barack Obama announced in a Jan. 17 speech on U.S. intelligence gathering.

White House Counselor John Podesta, grounded by snow in Washington, delivered his keynote address and took questions over the phone. But Secretary of Commerce Penny Pritzker was on hand, as were MIT President L. Rafael Reif and a host of computer scientists from MIT, Harvard University, and Microsoft Research, who spoke about the technical challenges of protecting privacy in big data sets.

In his brief opening remarks, Reif mentioned the promise of big data and the difficulties that managing it responsibly pose, and he offered the example of MIT’s online-learning initiative, MITx, to illustrate both. “We want to study the huge quantities of data about how MITx students interact with our digital courses,” he said. “We want to measure what really works. We want to use what we learn to improve the way we teach — and to advance the science of teaching overall.”

But, Reif said, the question of how to protect the privacy of MITx students runs into difficulty right out of the gate. “MITx student data are governed by the Family Educational Rights and Privacy Act, or FERPA,” he said. But who counts as an MITx student? “Those who register, but never view course content? Those who view about half of the course content? Those who explore the course deeply, but don’t take the final exam? Or only those who actually earn a certificate?”

Podesta emphasized the history of privacy protection in the U.S., particularly the principles that undergird the Privacy Act of 1974. Those principles, he said, had been “refined” by the Consumer Privacy Bill of Rights that the White House presented in 2012 — whose development was led by one of the workshop’s organizers, Daniel Weitzner, now a research scientist in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). In 2011 and 2012, Weitzner served as the nation’s deputy chief technology officer.

The power of data

Of fundamental concern in the era of big data, Podesta said, is the shift from “predicated analysis of data — that is, using data to find something we already know that we’re looking for — to nonpredicated, or pattern-based, searches — using data to find patterns that reveal new insights.”

That concern came into sharper relief during the question-and-answer session, when Podesta was asked whether nonpredicated analysis was at odds with the Fourth Amendment, which requires probable cause for search and seizure.

“That’s what this study is trying to accomplish,” Podesta replied, “which is to take on board the effects of new technology and the questions about whether there is something new and different with respect to the jurisprudence around the Fourth Amendment that has developed over the years and that challenges some of the decisions that have been rendered by the Supreme Court.”

The next speaker was Cynthia Dwork, a distinguished scientist at Microsoft Research and a pioneer of “differential privacy,” the most mathematically rigorous notion of data privacy. The challenge that differential privacy is intended to meet, Dwork explained, is illustrated by a 2008 study by a pair of University of Texas researchers who analyzed the supposedly anonymous customer data released in support of a competition that sought to improve Netflix’s movie-recommendation engine. The UT researchers showed that correlating the rental dates of only three Netflix movies with the dates of posts on the Internet Movie Database was, on average, enough to uniquely identify a user in the data set.

Differential privacy proposes that a computation performed on a database — determining, say, the percentage of fans of “The Godfather” who also liked “Goodfellas” — is privacy-preserving if it yields virtually the same result whether or not the database contains any one person. That definition has led to the development of techniques that can trade some computational accuracy for an arbitrarily small difference in the results of the computation — a difference designated “epsilon.”

The question, Dwork explained, is how small this difference needs to be. That’s something the public needs to decide for itself, she argued, although she did make a few policy recommendations: that anyone who publishes a data analysis should also publish its epsilon, and that anyone who publishes data with an epsilon of infinity — guaranteeing that anyone in the data set can be identified — should be fined.

The limitations of privacy

The rest of the workshop’s technical discussions were divided between two panels. The first convened five CSAIL researchers whose work touches on the analysis of large data sets. John Guttag, the Dugald C. Jackson Professor of Computer Science and Engineering, who researches algorithms for finding diagnostically useful patterns in medical data, set the tone when he said, “People think the public fears loss of privacy. I have my real doubts about some of this. I think most people actually fear death, or death of a loved one, more than they do loss of privacy.”

Guttag described a three-year research project undertaken by his graduate student Jenna Wiens, who developed an algorithm that could identify patients at risk for bacterial infection from a variety of data collected by hospitals. “This work could not have been done with de-identified data,” Guttag said. “You need to know the home ZIP code of the patient: That turns out to be an important factor [along with] the room the patient was in, who else was in that room, who was in that room before the patient.”

None of the other panelists were as outspoken as Guttag, but Manolis Kellis, an associate professor of computer science, explained that the biological pathways that lead from particular genetic variations to incidence of disease are so complex that researchers, like him, who are trying to identify them require a huge amount of data to filter out all the noise. Indeed, he argued, the correlation between the volume of available genomic data and the pace of biological discovery is sharply inflected: Up to a certain point, adding more data yields little new insight, but beyond that point, the rate of useful discovery is exponential.

The importance of trust

Pritzker opened the second half of the workshop. “The American economy has always been grounded in the free flow of data and information,” she said. “I know the power of commerce data firsthand: I used Census Bureau data to launch my first business 25 years ago. My team needed to know the right places to build senior living centers, and the Census Bureau was critical to our decision-making.”

Pritzker cited a report by the McKinsey management consultancy that examined the economic potential of open data in seven industries: education, transportation, consumer products, electricity, oil and gas, health care, and consumer finance. “McKinsey’s analysis showed that open data in these sectors could help unlock $3 trillion in additional value to the global economy,” she said. “And yet, all of this potential hinges on one thing: trust.”

The researchers on the second panel discussed some of the mechanisms that might help secure that trust. The first three speakers — Shafi Goldwasser, Nickolai Zeldovich, and Vinod Vaikuntanathan, all professors in MIT’s Department of Electrical Engineering and Computer Science — discussed cryptographic schemes that enable remote servers to perform computations on encrypted data without actually decrypting it.

Zeldovich described the simplest but, as yet, most practical version of the idea, in which data is wrapped in successively more complex layers of encryption, each of which permits a different type of computation. Depending on the type of query a server is to perform, it can peel away layers of encryption until it arrives at data it can compute on. In experiments, Zeldovich said, this system increased the transaction time of database queries by a relatively modest 30 percent.

Goldwasser described a more complex system in which multiple servers — those of various federal agencies and private hospitals in one example; those of financial institutions and a government watchdog in another — exchange encrypted information. Her group, she explained, has proven that as long as a majority of the participants are honest, such “multiparty computing” schemes can allow each server to specify just the data that it wants to release to the others, without inadvertently leaking information it hopes to protect.

Vaikuntanathan reviewed recent progress on homomorphic encryption, in which a user would send encrypted data to a server that would, without decrypting it, process it and send back a still-encrypted result. Special-purpose homomorphic-encryption schemes have been developed, but Vaikuntanathan described his own group’s research toward the elusive goal of a practical scheme that would allow the server to execute any algorithm at all on the encrypted data.

In the end, the day’s discussions may not have yielded complete answers to the weighty questions that Podesta raised in opening the conference. But it did provide ample evidence of why MIT has been, as he put it, “the cradle for so many game-changing technologies.”