EECS Department Head Anantha Chandrakasan announced to EECS faculty today the appointment of Professor David Perreault as EECS Associate Department Head. Chandrakasan prefaced this announcement with the news of the appointment by School of Engineering Dean Ian Waitz of Professor Munther Dahleh, EECS Associate Department Head since July, 2011, as the Acting Director of the Engineering Systems Division (ESD) at MIT and Director-designate for a newly proposed organization focusing on socio-technical systems, information and decision systems, and statistics. Read more about Prof. Dahleh’s appointment in the MIT News Office Nov. 26, 2013 announcement.

Newly appointed EECS Associate Department Head David Perreault has been a member of the MIT faculty since 2001 and is a member of the Research Laboratory of Electronics and the Microsystems Technology Laboratories. Known internationally for his contributions to design and application of power electronics, Prof. Perrault is particularly cited for his contributions to the development of power converters operating at very high frequencies — providing benefit in both efficiency and performance in the areas of renewable energy, lighting communications, computation and transportation.

Three startup companies have been founded based on research in Prof. Perreault’s group, including Eta Devices, a startup company, which he co-founded with Joel Dawson to focus on high-efficiency RF power amplifiers. Prof. Perreault and his students have been recognized with many awards including six IEEE prize paper awards. He has served in numerous professional roles including Administrative Committee of the IEEE Power Electronics Society from 2002-2011 and as Technical Program Co-Chair of the 2009 IEEE Energy Conversion Congress and Exposition. In addition, David Perreault service contributions to MIT include his serving as the EECS Department Area III chair from 2008-2012, as an Associate Director of MTL during 2012 and as a member of the RLE Board.

On accepting this appointment, Prof. Perreault said: “This is a very exciting time in EECS, with tremendous advances being pioneered in areas ranging from energy to communications to biomedical systems.” Noting the unprecedented opportunities for students and faculty to shape the future, David Perreault said, “I look forward to working together with faculty, staff and students to create the best environment possible for education and innovation.” [Photo: David Perreault. credit: Greg Hren/Research Laboratory of Electronics, RLE at MIT]

The EECS Department is pleased to showcase this year's SuperUROP research projects. The fall SuperUROP poster presentations will be held on Thursday, December 5 in two sessions: 4:00 - 5:00PM and 5:10 - 6:10PM in room 34-401. Stay from 6:10 to 6:30PM for Networking.

We invite all interested and/or potential SuperUROP students to attend and support this work. Reservations are no longer being accepted, but you are welcome to attend -- as long as there is adequate event space.

Microsystems Technology Laboratories (MTL) Principal Research Scientist Luis Velasquez-Garcia, with members of his research group has developed a new way to perform x-rays that not only includes soft tissue, but is streamlined to portable dimension cutting the dose and overall expense typical for current x-ray machines. The Velasquez-Garcia group is presenting their work at the 13th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2013), being held Dec. 3 to 6 in London. [Photo: A sample X-ray of a human wrist demonstrates the system's ability to reveal soft-tissue structures and very fine detail. Courtesy of Velasquez-Garcia Research Group.]

Read more in the Dec. 4, 2013 MIT News Office article by David L. Chandler titled "A leap forward in X-ray technology - New system could provide detailed images — even of soft tissue — from a lightweight, portable device," also posted below.

X-rays transformed medicine a century ago by providing a noninvasive way to detect internal structures in the body. Still, they have limitations: X-rays cannot image the body’s soft tissues, except with the use of contrast-enhancing agents that must be swallowed or injected, and their resolution is limited. But a new approach developed by researchers at MIT and Massachusetts General Hospital (MGH) could dramatically change that, enabling the most detailed images ever — including clear views of soft tissue without any need for contrast agents. The work will be presented by MIT postdoc Shuo Chen at the 13th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2013), being held Dec. 3 to 6 in London.

The new technology “could make X-rays ubiquitous, because of its higher resolution, the fact that the dose would be smaller and the hardware smaller, cheaper, and more capable than current X-rays,” says Luis Velásquez-García, a principal research scientist at MIT’s Microsystems Technology Laboratories and senior author of the PowerMEMS paper.

Velásquez-García says that while conventional X-ray systems show little or no structure in most soft tissues — including all of the body’s major organ systems — the new system would show these in great detail. A test the team performed with an eye from a cadaver using X-rays from a particle accelerator clearly shows “all the structures, the lens and the cornea,” he says. “In time we are confident our system will be able to achieve such resolution with a far simpler and cheaper device.” [Photo: A test device built at MIT as proof-of-principle for the new, higher-resolution X-ray system, using a vacuum chamber that measures 8 inches across. The team expects that eventual production models would be substantially smaller. Courtesy Velasquez-Garcia Research Group.]

The key is to produce coherent beams of X-rays from an array of micron-sized point sources, instead of a spread from a single, large point as in conventional systems, Velásquez-García explains. The team’s approach includes developing hardware that is an innovative application of batch microfabrication processes used to make microchips for computers and electronic devices.

Using these methods — alternating between depositing layers of material and selectively etching the material away — the MIT researchers have produced a nanostructured surface with an array of tiny tips, each of which can emit a beam of electrons. These, in turn, pass through a microstructured plate that emits a beam of X-rays.

Using the first version of the cathode, the team was able to capture high-resolution absorption images of samples where fine soft-tissue structures are clearly visible. “This is very exciting,” Velásquez-García says. “We just started, but we are confident we are on the right path.”

The resulting coherent beam of X-rays from the optimized cathode chip would be equivalent to something that can now be produced only by “incredibly expensive” systems at linear particle accelerators, Velásquez-García says. But those facilities have demonstrated the diagnostic power of the images they can produce — for example, clearly revealing the presence of a cancerous tumor by showing the details of the blood vessels supplying it. Similarly, an image of a knee reveals all the ligaments, muscle attachments, and fine details of the bone structures that cannot be seen at all on conventional X-rays.

“You can’t have a linear accelerator in every hospital,” Velásquez-García says. But the new system could potentially improve the resolution of X-ray imagery by a factor of 100 with hardware that costs orders of magnitude less, he says.

Even when soft tissue can be imaged conventionally by adding contrast agents such as barium, the use of those agents takes extra time, and the agents themselves can pose risks, he says. And because the new system is electronic — today’s thermionic systems take time to heat up — it can be switched on and off much faster, resulting in a much lower dose of radiation to the patient, Velásquez-García says.

He says the technology could also have applications beyond the medical field. For example, X-rays are used to check for defects in composite materials; the portability of the new system could allow more widespread use of such safety measures. The new system could also be useful in airport screening of baggage, where its ability to distinguish among liquids could make it much easier for agents to differentiate a harmless bottle of shampoo from a container of explosive material or a hazardous chemical.

The test device the team built, working with Rajiv Gupta of MGH, is housed in an 8-inch metal cube, about the size of a shoebox. The team expects to spend two to three years refining and improving the design, Velásquez-García says; commercial versions could be available within a few years after that.

Christopher Holland, a principal scientist at Micro Science Engineering Laboratories in Menlo Park, Calif., who was not involved in this work, says, “The approach being pursued by the authors of this article and others on the MIT team is novel and has significant potential for imaging soft tissue using X-rays.” He cautions, “The demonstration in this paper is only a laboratory demonstration and not yet portable,” but says it is “a steppingstone on that path.”

The research, which also included MIT postdoc Frances Hill and graduate student Eric Heubel, was funded by the Defense Advanced Research Projects Agency.

EECS Department Head Anantha Chandrakasan announced today the appointment of Professor Daniela Rus as the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science. The Chair was established in 1999 by Andrew and Erna to recognize significant contributions in the field of communications and signal processing. Prof. Ronald Rivest was the first chair holder of the Viterbi Professorship.

Professor Rus, the Director of MIT’s Computer Science and Artificial Intelligence Laboratory, has made seminal contributions to motion planning, controlling, and fielding autonomous robots. Her research covers a broad spectrum of technical problems related to self-organizing networks of robots, including robot design, control, locomotion, manipulation, and high-level planning and control for groups of robots. Her work on shape shifting robots is foundational for the field of modular self-reconfiguring robot systems, where the objective is to design robot modules and planning and control algorithms that enable the resulting robot systems to self-organize as the shape best suited for the sensing, navigation, or manipulation needs of a task. Her work has contributed several new robot platforms with novel capabilities and algorithms for controlling networks of robots. (See the links to the media coverage of the numerous robotic systems developed by Prof. Rus.)

In his announcement, Prof. Chandrakasan noted Prof. Rus’ dedication as an educator, saying, “She is also an outstanding educator and a wonderful mentor to her students.” Prof. Rus developed, in collaboration with Professor Seth Teller, two very popular courses for the Robotics Science and Systems sequence (6.141 and 6.142). Two offerings of the advanced course (6.142) resulted in refereed conference publications authored with the class that were nominated as best papers at the premier conferences in robotics, ICRA and IROS. The first paper described a class project on an autonomous greenhouse and the second paper described a class project of assembling Ikea furniture with robots. More recently, Professor Rus has worked with Professor Erik Demaine and Chuck Hoberman to create an innovative course that explores the role of computation in mechanical innovation.

Professor Rus has also devoted significant time to robotics education outside of MIT. As education co-chair of the Robotics and Automation Society, she spearheaded an effort to create an electronic repository of robotics teaching materials with the goal of enabling non-experts in the field to offer undergraduate robotics courses. She has also played a leadership role in the field, serving on the Long Range Planning Committee of IEEE’s Robotics and Automation Society, as general chair for several robotics conferences including the International Symposium on Experimental Robotics and Algorithmic Foundations of Robotics, and in the roles of a program committee member, associate editor, and technical contributor for all the premier robotics journals and conferences. Her contributions have been recognized with a MacArthur fellowship in 2002 while she was an associate professor at Dartmouth College, where she directed the Dartmouth Robotics Laboratory, which she founded in 1994.

Cited for contributions in wireless networking, and contributions to theory and practice of synchronization in concurrent programming, respectively

Professors Dina Katabi and Nir N. Shavit have been elected to 2013 Fellow by the Association of Computing Machinery (ACM). As part of a select 1% of ACM membership, Fellows are recognized “for their contributions to computing that are driving innovations across multiple domains and disciplines - accelerating the digital revolution and impacting every dimension of how we live work and play.” Candidates for Fellow must have five years of continuous professional membership.

Professor Katabi is cited by the ACM "For contributions in cross-layer wireless networking, wireless network coding, and Internet congestion control". As one of the top computer science researchers working in the field of wireless networks, Dina has delivered multiple breakthrough results in her field including new methods for resolving wireless interference and increasing the throughput of WiFi and cellular networks. She has also produced important results in multidisciplinary areas including the sparse Fourier Transform and wireless network coding. Recently, Dina was selected as a MacArthur Fellow and she received the 2013 ACM Grace Murray Hopper Award in June.

Professor Shavit has been elected as an ACM Fellow with the following citation: “For contributions to the theory and practice of synchronization in concurrent programming.” Nir's research has focused on multiprocessor computing--from its mathematical foundations to its practical implementations. As multicore machines have gone mainstream, a number of his past 'theoretical' algorithms, paradigms and data structures algorithms have become essential elements in compilers and concurrency libraries distributed to tens of millions of desktops around the world. For his theoretical work on applying tools from algebraic topology to model shared memory computability, Nir was awarded the 2004 Gödel Prize in theoretical computer science, and in 2012, he was awarded the Dijkstra prize for the introduction and first implementation of software transactional memory.

Further reading:
ACM Names Fellows for Computing Advances that Are Transforming Science and Society

Professor Alan Willsky, has been selected to receive the 2013 SPS Society Award of the IEEE Signal Processing Society (SPS). Willsky is the Edwin Sibley Webster professor of electrical engineering and computer science and director of the MIT Laboratory for Information and Decision Systems (LIDS) at MIT.

The SPS Society Award is the highest award bestowed by the IEEE Signal Processing Society, and honors outstanding technical contributions in a field within its scope and outstanding leadership in that field. Prof. Willskty is cited "For fundamental contributions to probabilistic modeling and for pioneering work in the development and application of multi-resolution statistical methods." The awards ceremony will take place at the upcoming ICASSP 2014 conference in Florence, Italy, in May 2014.

Over the years, Professor Willsky has performed path-breaking research in areas as diverse as failure detection in dynamic systems, tomography, computer vision, and signal processing. Willsky's text, co-authored with Professor Alan Oppenheim, has remained as one of the leading textbooks on signals and systems for more than 30 years.  Alan is a member of the National Academy of Engineering, and he has received numerous awards for his research from organizations ranging from the American Automatic Control Council to the IEEE and several of its societies, including the IEEE Donald G. Fink Award in recognition of his widely cited paper on multi-resolution statistical methods. 

Professor Piotr Indykand members of his group in the Computer Science and Artificial Intelligence Lab(CSAIL) have developed an algorithm that betters his (and Prof. Dina Katabi's) work to develop a faster than fast Fourier Transform in 2012. The new algorithm that uses the minimum possible number of samples to analyze signals has the potential to allow advances in medical devices such as magnetic resonance imaging (MRI) and nuclear magnetic resonance (NMR) machines to scan patients.

Read more in the Dec. 11, 2013 MIT News Office article by Helen Knight titled "Leaner Fourier transforms - New algorithm can separate signals into their individual frequencies using a minimal number of samples," also posted below. [Image credit: Christine Daniloff, MIT News Office].

The fast Fourier transform, one of the most important algorithms of the 20th century, revolutionized signal processing. The algorithm allowed computers to quickly perform Fourier transforms — fundamental operations that separate signals into their individual frequencies — leading to developments in audio and video engineering and digital data compression.

But ever since its development in the 1960s, computer scientists have been searching for an algorithm to better it.

Last year MIT researchers Piotr Indyk and Dina Katabi did just that, unveiling an algorithm that in some circumstances can perform Fourier transforms hundreds of times more quickly than the fast Fourier transform (FFT).

Now Indyk, a professor of computer science and engineering and a member of the Theory of Computation Group within the Computer Science and Artificial Intelligence Laboratory (CSAIL), and his team have gone a step further, significantly reducing the number of samples that must be taken from a given signal in order to perform a Fourier transform operation.

Close to theoretical minimum

In a paper to be presented at the ACM-SIAM Symposium on Discrete Algorithms in January, Indyk, postdoc Michael Kapralov, and former student Eric Price will reveal an algorithm that can perform Fourier transforms using close to the theoretical minimum number of samples. They have also bettered even this, developing an algorithm that uses the minimum possible number of signal samples.

This could significantly reduce the time it takes medical devices such as magnetic resonance imaging (MRI) and nuclear magnetic resonance (NMR) machines to scan patients, or allow astronomers to take more detailed images of the universe, Indyk says.

The Fourier transform is a fundamental mathematical notion that allows signals to be broken down into their component parts. When you listen to someone speak, for example, you can hear a dominant tone, which is the principal frequency in their voice. “But there are many other underlying frequencies, which is why the human voice is not a single tone, it’s much richer than that,” Indyk says. “So in order to understand what the spectrum looks like, we need to decompose the sounds into their basic frequencies, and that is exactly what the Fourier transform does.”

The development of the FFT automated this process for the first time, allowing computers to rapidly manipulate and compress digital signals into a more manageable form. This is possible because not all of the frequencies within a digital signal are equal. Indeed, in nature many signals contain just a few dominant frequencies and a number of far less important ones, which can be safely disregarded. These are known as sparse signals.

“In real life, often when you look at a signal, there are only a small number of frequencies that dominate the spectrum,” Indyk says. “So we can compress [the signal] by keeping only the top 10 percent of these.”

Indyk and Katabi’s previous work focused on the length of time their algorithm needed to perform a sparse Fourier transform operation. However, in many applications, the number of samples the algorithm must take of the signal can be as important as its running time.

Applications in medical imaging, astronomy

One such example is in MRI scanning, Indyk says. “The device acquires Fourier samples, basically snapshots of the body lying inside the machine, which it uses to recover the inner structure of the body,” he says. “In this situation, the number of samples taken is directly proportionate to the amount of time that the patient has to spend in the machine.”

So by allowing the MRI scanner to produce an image of the body using a fraction of the samples needed by existing devices, it could significantly reduce the time patients must spend lying still inside the narrow, noisy machines.

The team is also investigating the idea of using the new sparse Fourier transform algorithm in astronomy. They are working with researchers at the MIT Haystack Observatory, who specialize in radio astronomy, to use the system in interferometry, in which signals from an array of telescopes are combined to produce a single, high-resolution image of space. Applying the sparse Fourier transform algorithm to the telescope signals would reduce the number of observations needed to produce an image of the same quality, Indyk says.

“That’s important,” he says, “because these are really massive data sets, and to make matters worse, much of this data is distributed because there are several different, separated telescopes, and each of them acquires some of the information, and then it all has to be sent to the same place to be processed.”

What’s more, radio telescopes are extremely expensive to build, so an algorithm that allows astronomers to use fewer of them, or to obtain better quality images from the same number of sensors, could be extremely important, he says.

Martin Strauss, a professor of mathematics, electrical engineering, and computer science at the University of Michigan, who develops fundamental algorithms for applications such as signal processing and massive data sets, says work by Indyk and others makes sparse Fourier transform algorithms advantageous over the celebrated FFT on a larger class of problems than before. “The current paper squeezes out nearly all [of the performance] that is possible with these methods,” he says.

Prof. Dina Katabi, principal investigator in the Computer Science and Artificial Intelligence Lab at MIT working with members of her research group (NETMIT) has developed a 3-D motion tracking system that has potential for gaming and far more.  

Read more in the CSAIL Dec. 12, 2013 article by Abby Abazorius appearing on the MIT News Office website titled "New system allows for high-accuracy, through-wall, 3-D motion tracking - Technology could revolutionize gaming, fall detection among the elderly, and more," also posted below in its entirety. 

Imagine playing a video game like Call of Duty or Battlefield and having the ability to lead your virtual army unit while moving freely throughout your house.

Gaming could become this realistic, thanks to new technology developed by Dina Katabi’s research group at the MIT Computer Science and Artificial Intelligence Lab (CSAIL) that allows for highly accurate, 3-D motion tracking. The new system, dubbed “WiTrack”, uses radio signals to track a person through walls and obstructions, pinpointing her 3-D location to within 10 to 20 centimeters — about the width of an adult hand.

The researchers will present their findings during the Usenix Symposium on Networked Systems Design and Implementation in April 2014.

“Today, if you are playing a game with the Xbox Kinect or Nintendo Wii, you have to stand right in front of your gaming console, which limits the types of games you can play,” says Katabi, a professor of computer science and engineering and co-director of the MIT Center for Wireless Networks and Mobile Computing. “Imagine playing an interactive video game that transforms your entire home into a virtual world. The game console tracks you as you run down real hallways away from video game enemies, or as you hide from other players behind couches and walls. This is what WiTrack can bring to video gaming.”

Earlier this year, Katabi and her graduate student Fadel Adib unveiled WiVi, a system that detects humans through walls and can track the direction of their movement using WiFi signals. Based on this earlier work, Katabi and Adib developed WiTrack in collaboration with Rob Miller, a professor of computer science and engineering, and graduate student Zach Kabelac. In comparison to WiVi, WiTrack has significantly higher accuracy and can track both two-dimensional and three-dimensional movement using specialized radio waves, as opposed to WiFi signals.

WiTrack operates by tracking specialized radio signals reflected off a person’s body to pinpoint location and movement. The system uses multiple antennas: one for transmitting signals and three for receiving. The system then builds a geometric model of the user’s location by transmitting signals between the antennas and using the reflections off a person’s body to estimate the distance between the antennas and the user. WiTrack is able to locate motion with significantly increased accuracy, as opposed to tracking devices that rely on wireless signals, according to Adib.

“Because of the limited bandwidth, you cannot get very high location accuracy using WiFi signals,” Adib says. “WiTrack transmits a very low-power radio signal, 100 times smaller than WiFi and 1,000 times smaller than what your cell phone can transmit. But the signal is structured in a particular way to measure the time from when the signal was transmitted until the reflections come back. WiTrack has a geometric model that maps reflection delays to the exact location of the person. The model can also eliminate reflections off walls and furniture to allow us to focus on tracking human motion.”

In other motion-tracking systems, users must carry a wireless device or stand directly in front of the sensing device in order for the device to pick up movement. By using specialized radio signals, WiTrack frees users from wireless devices and allows them to roam spaces freely while still providing high-accuracy localization.

The system’s ability to track motion through obstructions could make it particularly useful not only in gaming, but also in tracking elderly patients at high risk of falling. Current approaches to fall detection require individuals to continuously wear sensors or install cameras in the person’s home. While WiTrack does not require individuals to wear sensors or install cameras, it can still detect falls with very high accuracy.

The ability of the WiTrack system to perform high-accuracy localization without expending enormous amounts of computational power is a promising new development in motion-tracking technology, according to Victor Bahl, a principal researcher and director of mobility and networking research at Microsoft Research.

“Motion tracking has generally been accomplished by analyzing images captured from strategically placed cameras inside the room. A limitation of such systems is that they only work when the moving object is directly in the camera’s line of sight,” Bahl says. “Another problem is [that] image analysis is a computationally heavyweight operation.”

“The technology Professor Katabi and her students have developed does not have these limitations,” he adds. “Their system detects movement without requiring a huge amount of computational power, and without having to be placed inside the room. The surprising thing is that it is very accurate. There is still more research to be done, but the approach is promising.”

The team is currently working on advancing the WiTrack system so that it can track more than one person in motion at a time. The researchers believe the system should be easily adaptable to commercial settings. “The system is not expensive or time-consuming to produce and it could be miniaturized for easier production and use,” Kabelac says.

For more information on WiTrack, please visit: http://witrack.csail.mit.edu/.

SuperUROP research presentations on Dec. 5 garner large crowd of students, faculty and industry visitors
By Lauren Clark

On Dec. 5, Paul Bassett ’85 traveled to Cambridge from Austin, Tex., where he works as a senior director of technology for the wireless communications giant Qualcomm. He wound his way through a crowd assembled in the Grier Room at MIT, where nearly 80 undergraduates in electrical engineering and computer science (EECS) presented posters on cutting-edge research projects. Qualcomm sponsors several of those students as part of the MIT SuperUROP program.

Under the leadership of EECS department head Anantha P. Chandrakasan, the Joseph F. and Nancy P. Keithley Professor of Electrical Engineering, and MIT’s Undergraduate Research Opportunities Program, SuperUROP launched last year as a way to offer undergraduates a deep dive into research.

SuperUROP pairs students with a faculty member for an entire academic year and includes a two-semester course on undergraduate research. Participants expect to produce prototypes or publication-worthy results, and their projects often evolve into graduate theses, startup plans, or industry positions.

“Here is a group of top-notch engineering students working in all sorts of different areas,” Bassett said. “I can scan through the projects and identify the ones that align with what the company’s going to care about in the future. As an engineering manager, my goal is the future engineers as much as the actual research. Qualcomm wants MIT to be working on interesting research that will be applicable to future products — but MIT is also going to be turning out the engineers who are going to help us build those products.”

SuperUROP brings students and industry sponsors together in mutually beneficial engagement. In addition to funding projects through the Research and Innovation Scholars Program, sponsors mentor students, give talks about their companies’ technologies, and work with faculty to set research directions. Students, meanwhile, get valuable insight from professionals working on real-world products and services.

Sowing the seeds for future engineering leaders

“SuperUROP is a tremendous opportunity for students and companies to make connections that foster future innovations and that launch the careers of engineering leaders,” said entrepreneur Desh Deshpande, a member of the MIT Corporation who attended the poster session.

Benoit Landry, an EECS senior from Montreal, is sponsored by the automotive technology company DENSO and has enjoyed discussions with several other industry partners of SuperUROP. Under the guidance of Russ Tedrake, an associate professor of computer science and engineering, Landry is developing control systems that could enhance the agility of unmanned aerial vehicles by, for example, allowing a small drone to rapidly change its direction by bouncing off of a wall.

“We can all benefit from Cisco or Qualcomm coming in and giving us a talk, whether they’re directly funding our research or not,” Landry said. At informal dinners with sponsors, he added, “You’ve got a bunch of people who feel very strongly about engineering, sitting around a table and talking about research. It’s very empowering to talk to all these people who are incredibly talented. They come to tell you that what you’re working on is worth working on. It’s a big boost [for the students’] motivation.”

EECS junior Rose Abramson, who is working on technology that could shrink the scale of transistors made from silicon alternatives to below 10 nanometers, said, “People from a lot of different industries come up to you and want to talk about your work because it’s so interesting.” Her sponsor, the semiconductor company MediaTek Inc., has been receptive to the SuperUROP students. “They really like hearing about the work, and they come to many of the events,” said Abramson, who grew up near San Francisco.

The funding Abramson has received through her MediaTek Research and Innovation Scholarship has enabled her to fabricate devices in the clean rooms at MIT’s Microsystems Technology Laboratory (MTL) — an expensive activity that usually isn’t open to undergraduates, but which was made possible through generous support from MTL for the SuperUROP program. 

“Most people only start fabricating once they get into graduate school,” said Abramson, whose faculty advisor is MTL director Jesús del Alamo, the Donner Professor of Science. “It’s really cool to be able to actually see how these things are put together.”

Collaboration linking Industry, Faculty and Students

“One of my goals is to connect the sponsors’ research interests with faculty, so that the relationship between the faculty and the company can carry forward year over year,” said Ted Equi, a 30-year veteran of the semiconductor industry and the industrial liaison for SuperUROP. “The beauty of this program is that it provides an infrastructure for getting the projects generated. We solicit ideas from industry and from faculty, and then the students write the proposal.”

EECS junior Qui Nguyen had never thought of working on a smartphone app that monitors a medical disorder before she came across one of Chandrakasan’s research projects while applying for SuperUROP this fall. “I was interested in it because the application is useful and tangible, and it’s an interesting area in computer science,” said Nguyen, who is sponsored by the contract electronics manufacturer Foxconn.

Nguyen working with several other students on her team, aims to create a smartphone app that patients and doctors can use to reliably track vitiligo, a skin condition characterized by white patches where pigment-producing cells have been destroyed. A patient will typically have several affected areas on the body, so Nguyen’s task is to develop an image-processing algorithm that can automatically sort by area the photos that patients take. She hopes the application can extend to tracking other skin conditions as well.

EECS senior Kristjan Eerik Kaseniit’s synthetic biology project was already underway before becoming a SuperUROP. Kaseniit said he is trying to “program biological cells into behaving sort of like robots.” Strands of RNA placed within the cells perform computations that could, for example, detect cancer.

While the project’s results prior to SuperUROP were promising, Kaseniit said, “Now I can really go in-depth. If you’re doing a regular UROP, the commitment is sort of different. But now I go to lab as often as I can, because I’m more invested in this project. The learning curve is exponential — it's very slow in the beginning, but then it speeds up a lot. I’m gaining momentum, and because I'm able to continue over IAP and the next semester, the momentum’s not lost.”

Kaseniit is considering building upon his SuperUROP, which is sponsored by Draper Laboratory and supervised by associate professor of biological engineering Ron Weiss, in the new Computer Science and Molecular Biology Masters of Engineering program after he completes a year of compulsory military service in his native Estonia.

Another EECS senior, David Xiao, is trying to decide whether to go into research or industry after graduation. Sponsored by Quanta Computer, the Brentwood, N.H., native is working with associate professor Rob Miller of the Computer Science and Artificial Intelligence Laboratory to create online games for teaching software engineering. Their goal is to deploy the games in the spring edX class 6.005x: Elements of Software Construction.

“SuperUROP offers an interesting balance of research and industry,” Xiao said. “Andreesen Horowitz venture capitalist Peter Levine shared some interesting insights about how startups work. There are [students] here who probably won’t end up doing research. Either way, the program is useful.”

MIT Chancellor Eric Grimson, the Bernard Gordon Professor of Medical Engineering, who attended the poster session, agreed with Xiao. “The experiences students obtain by focusing on a cutting-edge research problem over an extended period of time will be invaluable to them no matter what career path they follow,” he said.

Over the buzz of the presentations taking place in the Grier Room, John Howard explained why his company became involved with SuperUROP. He is the director of advanced materials development at Lab 126, a consumer electronics subsidiary of Amazon.

Research that's relevant

“What we’re getting is an opportunity to invest in students and get to know them,” Howard said. “It’s extremely important to us to find the best and the brightest.” In addition, he said, the work the students presented seemed relevant to issues that industry is working on: “They’re actually trying to take [the research] someplace. It’s nice to see.”

In addition to Amazon, Andreesen Horowitz, Cisco, DENSO, Draper Laboratory, Foxconn, MediaTek, Qualcomm, and Quanta Computer, SuperUROP industry sponsors include Actifio, Analog Devices, eBay Inc., Google, Texas Instruments, TIBCO Software Inc., and VMWare. Individual supporters include Robert Fano, Dinarte Morais and Paul Rosenblum, as well as several anonymous donors.

Prof. Mildred Dresselhaus, Institute professor emerita and faculty member in the Electrical Engineering and Computer Science and Physics Departments at MIT, received the Materials Research Society von Hippel Award in recognition of her work and close association with Prof. von Hippel.

Read the fascinating story about Dresselhaus' support by von Hippel in selecting carbon as her area of focus when she settled in as a young professor at MIT in the 1960s. See the MIT News Office Dec. 12, 2013 article by Denis Paiste titled "Remembering Arthur R. von Hippel - MIT Institute Professor Emeritus Mildred Dresselhaus recalls mentor’s influence as she receives award in his name," also posted below in its entirety.

Arthur R. von Hippel embodied scientific curiosity and mentorship and shared her passion for music, MIT Institute Professor Emeritus Mildred S. Dresselhaus said Wednesday night in accepting the Materials Research Society award named in his honor. The Materials Research Society has conferred the MRS Von Hippel Award annually since 1976, when it was given to von Hippel. Dresselhaus received the award for her pioneering contributions to the fundamental science of carbon-based and other low-electron-density materials, her leadership in energy and science policy, and her exemplary mentoring of young scientists.

Von Hippel encouraged Dresselhaus, made her part of his string quartet, and remained her friend from the time she joined MIT’s Lincoln Lab in 1960 until his death in 2003 at 105. Dresselhaus became a professor at MIT in 1968.

Dresselhaus said she had good luck in finding mentors over her long career: future Nobel Laureate Rosalyn Yalow, while Dresselhaus was an undergraduate at Hunter College in New York; Enrico Fermi, while she was a graduate student at the University of Chicago; and von Hippel at MIT. (Dresselhaus received the Enrico Fermi award from President Barack Obama in 2012.)

Dresselhaus was encouraged to “work on something that was interesting to me and that people didn’t know anything about,” she said. “That was the 1960s. Carbon science had essentially nobody working in there, so von Hippel thought that was a pretty good topic to be working on.” He encouraged her to work on graphite, a simple form of carbon.

“The carbon-carbon bond is the strongest bond in nature,” Dresselhaus said. “We wouldn’t have a space industry without the carbon-carbon bond.”

Dresselhaus’s work led her to perform experiments with circularly polarized light from a helium-neon laser — a new technology in the 1960s — that established the location of electrons and holes, or electron vacancies, in graphite. She went on to study superconductivity in layered carbon and potassium compounds, and then fullerenes and carbon nanotubes, writing books on the latter two. At the prompting of government researchers, she wrote “Graphite Fibers and Filaments.” “We became experts in carbon fibers for a while,” she said.

In later spectroscopy experiments, Dresselhaus and colleagues showed that carbon nanotubes could be either metallic or semiconducting. “Nanoscience has really benefited from all those ideas,” she said. Dresselhaus recalled that von Hippel, who worked in the lab until age 90, helped develop radar during World War II and was always interested in practical applications as well as theoretical research. “He liked complicated materials and was an expert in perovskites and ferroelectrics,” she said.

In answer to a question about women in science, Dresselhaus encouraged current faculty to be active mentors — as von Hippel was to her — and particularly to encourage young women to become scientists. Even before college, many young women are discouraged, she said, with questions such as “What is a pretty girl like you doing studying physics?” Faculty need to encourage young women to be successful in both their personal and their professional lives, and they can help by sharing their own personal quests to achieve balance, she said.

Materials Research Society President Orlando Auciello, of the University of Texas at Dallas, presented the award to Dresselhaus at the Grand Ballroom of the Sheraton Boston Hotel. The award includes a $10,000 cash prize.

Manolis Kellis, associate professor of computer science at MIT has teamed to combine work developing algorithms that predict how strands of RNA are likely to unfold with work to identify biologically meaningful RNA folds within living cells. Published in Nature this week, this work shows promised for understanding RNA machinery -- a major avenue towards understanding genetic and biological function in living cells. [Graphic: Understanding the mulitple functions of mRNA is aided by work of Kellis at MIT CSAIL and other MIT and UCSF teams. Courtesy of the research teams.]

Read more in the Dec. 15, 2013 MIT News Office article by Elizabeth Dougherty titled "Unusual suspects - Computer models plus observations of RNA inside a cell help scientists home in on a short list of interesting RNA ‘machines.’ Elizabeth Dougherty, MIT News correspondent," also posted below in its entirety.

DNA stores the information of life, proteins provide the action, and in between sits elusive RNA, which serves both as a database of information and as a molecular machine. RNA is more flexible than DNA, and its three-dimensional structures are more complex than proteins. When studied in the laboratory, RNA bends into so many convolutions that it is nearly impossible to tease out which folds are worthy of scientific inquiry and which can safely be ignored.

New collaborative work from computational biologists at MIT and experimental biologists at the University of California at San Francisco (UCSF), however, is easing that distinction by combining computational and experimental approaches to identifying biologically meaningful RNA folds. The work, published this week in Nature, could open the door to a better understanding of RNA machinery — which ranges from the ribosome, a molecular factory that manufactures proteins, to microRNAs and riboswitches, tiny devices that regulate gene expression, to long noncoding RNAs whose diverse functions are only beginning to be understood.

“There’s much that’s uncertain about RNA,” says co-author Manolis Kellis, an associate professor of computer science at MIT. “Our approach combining computational predictions and experimental measurements can really help us go in the direction of understanding the machinery behind the countless cellular processes that involve RNA.”

Predicting RNA folding

Similar to proteins, RNA folds into 3-D structures that carry out complex molecular functions. To begin studying this RNA machinery, Kellis and co-author Stefan Washietl, a former MIT postdoc who now heads a startup in Vienna, spent several years developing algorithms that predict how strands of RNA are likely to fold. They based their initial models on well-established properties of thermodynamic folding, using parameters that scientists had measured painstakingly over decades.

At the same time, senior author Jonathan Weissman and first author Silvi Rouskin of UCSF were devising a new technique to investigate how RNA strands fold inside a living cell. The technique applies a chemical, dimethyl sulfate, which binds with unfolded strands of RNA, but not with folded strands. To translate the data they gathered using this technique into RNA structures, they employed another algorithm written by Manolis and Washietl that had already been applied to experiments probing RNA in test tubes.

“This work is a major advance in being able to observe RNA folding in its native environment,” says John Rinn, an assistant professor of stem cell and regenerative biology at Harvard University who was not involved in this study. “Now, for the first time, we can globally survey what these structures look like in a cell.”

With this first look at the RNA structures that form in cells, the collaborators could answer a longstanding question: Does RNA fold the same way in cells as in test tubes, as proteins do? They found that, while experimental evidence from studies of RNA structures in test tubes matched Kellis’ computational predictions, observations in living cells did not. Of 23,412 RNA regions they sampled, only 3.9 percent form structures in the cell, compared with 24 percent in test tubes.

“The differences tell us that the system is not obeying the rules of thermodynamics in living cells,” Kellis says. “There is something that the cell is doing to change the folding pattern.”

Most valuable players

Further experimental investigation revealed that RNA inside an energy-depleted cell folds more readily, confirming the hypothesis: Cells are expending energy to allow only certain RNA folds to form, suggesting that those folds must be valuable to the cell.

This insight prompted Kellis and Washietl to study the evolutionary conservation of these structures across related species, to zoom in on the RNA folds likely to be most valuable. “The most interesting RNA folds have either remained unchanged or have changed rapidly over time, suggesting some sort of evolutionary pressure,” Kellis says.

The result is a short list of 259 functionally intriguing RNAs. The collaborators have already confirmed, through further experimental analysis, that three messenger RNAs from this list are likely to perform physiological functions, doubling the number of known functional mRNAs in yeast. “This combination of next-generation sequencing and computational analysis allows us to do biology much more quickly,” Weissman says.

This short list is particularly valuable to Rinn and others who study noncoding RNAs, since structure is at the core of its function. “We now have a lookup table for RNA structure that we could possibly use to start to infer categories of function for noncoding RNAs,” Rinn says. “This technique is a great proof of principle that could revolutionize our understanding of noncoding structures.”

These findings also lend credence to the computational models of RNA folding that Kellis and Washietl had created. “For those RNAs that actually matter, our models are accurate and useful,” Washietl says.

While this study focused on yeast, the researchers have already begun applying these techniques to mammalian cells. “The method is general, so there is great potential to uncover new biology, from yeast to human,” Washietl says.

The research was funded by the Center for RNA Systems Biology, which is supported by the National Institutes of Health, the Howard Hughes Medical Institute, and the National Science Foundation.

Sangeeta Bhatia, professor in MIT's Electrical Engineering and Computer Science Department and the Harvard MIT Health Sciences and Technology, has developed a noninvasive and quick test for the presence of blood clots using nanoparticles. This test could potentially be used in detecting other health threatening issues such as cancer.  Bhatia has published this work in the recent online ACS Nano.  Read more in the Technology ReviewDec. 17, 2013, article by Helen Knight, posted below.

Life-threatening blood clots can form in anyone who sits on a plane for a long time, is confined to bed while recovering from surgery, or takes certain medications.

There is no fast and easy way to diagnose these clots, which often remain undetected until they break free and cause a stroke or heart attack. However, new technology from MIT may soon change that: a team of engineers has developed a way to detect blood clots using a simple urine test.

The noninvasive diagnostic, described in a recent issue of the journal ACS Nano, relies on nanoparticles that detect the presence of thrombin, a key blood-­clotting factor. Such a system could be used to monitor patients who are at high risk for blood clots, says ­Sangeeta Bhatia, senior author of the paper and a professor of health sciences and technology and of electrical engineering and computer science.

Blood clotting is produced by a complex cascade of protein interactions, culminating in the formation of fibrin, a fibrous protein that seals wounds. Thrombin controls the last step of this process—the conversion of fibrinogen to fibrin.

Bhatia’s new test uses iron oxide nanoparticles, which the Food and Drug Administration has approved for human use, coated with peptides (short proteins) that are specialized to interact with thrombin. After being injected into mice, the nanoparticles travel throughout their bodies. When the particles encounter thrombin, the thrombin cleaves the peptides into fragments that are then excreted in the animals’ urine.

Once the urine is collected, the protein fragments can be identified by treating the sample with antibodies that latch onto them. The researchers showed that the quantity of these fragments found in the urine is directly proportional to the level of blood clotting in the mice’s lungs.

Bhatia says she envisions this test being used to screen patients who come to the emergency room complaining of symptoms that might indicate a blood clot, allowing doctors to rapidly triage such patients and determine if more tests are needed.

Another application is monitoring patients who are at high risk for a clot—for example, people who have to spend a lot of time in bed after an operation. The particles could also be adapted to monitor and diagnose cancer, or to track liver, pulmonary, and kidney fibrosis, Bhatia says.

Computer Science and Artificial Intelligence Laboratory's (CSAIL) Aude Oliva, associate professor of cognitive science at MIT's Brain and Cognitive Sciences working with her CSAIL colleagues including Antonio Torralba, associate professor in MIT's Electrical Engineering and Computer Science Department and also a member of in the MIT Computer Vision Group has developed an algorithm to slightly modify a person's face — making it more memorable without altering that person's overall appearance. The work, which was presented by the group at the International Conference on Computer Vision in Sydney, will be useful for online image identity for employment applications, for example.

Read more in the Dec. 18, 2013 MIT News Office article by Helen Knight titled "Never forget a face. New algorithm uses subtle changes to make a face more memorable without changing a person’s overall appearance," also posted below in its entirety.

Do you have a forgettable face? Many of us go to great lengths to make our faces more memorable, using makeup and hairstyles to give ourselves a more distinctive look.

Now your face could be instantly transformed into a more memorable one without the need for an expensive makeover, thanks to an algorithm developed by researchers in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).

The algorithm, which makes subtle changes to various points on the face to make it more memorable without changing a person’s overall appearance, was unveiled earlier this month at the International Conference on Computer Vision in Sydney.

“We want to modify the extent to which people will actually remember a face,” says lead author Aditya Khosla, a graduate student in the Computer Vision group within CSAIL. “This is a very subtle quality, because we don’t want to take your face and replace it with the most memorable one in our database, we want your face to still look like you.”

More memorable — or less The system could ultimately be used in a smartphone app to allow people to modify a digital image of their face before uploading it to their social networking pages. It could also be used for job applications, to create a digital version of an applicant’s face that will more readily stick in the minds of potential employers, says Khosla, who developed the algorithm with CSAIL principal research scientist Aude Oliva, the senior author of the paper, Antonio Torralba, an associate professor of electrical engineering and computer science, and graduate student Wilma Bainbridge.

Conversely, it could also be used to make faces appear less memorable, so that actors in the background of a television program or film do not distract viewers’ attention from the main actors, for example.

To develop the memorability algorithm, the team first fed the software a database of more than 2,000 images. Each of these images had been awarded a “memorability score,” based on the ability of human volunteers to remember the pictures. In this way the software was able to analyze the information to detect subtle trends in the features of these faces that made them more or less memorable to people.

The researchers then programmed the algorithm with a set of objectives — to make the face as memorable as possible, but without changing the identity of the person or altering their facial attributes, such as their age, gender, or overall attractiveness. Changing the width of a nose may make a face look much more distinctive, for example, but it could also completely alter how attractive the person is, and so would fail to meet the algorithm’s objectives.

When the system has a new face to modify, it first takes the image and generates thousands of copies, known as samples. Each of these samples contains tiny modifications to different parts of the face. The algorithm then analyzes how well each of these samples meets its objectives.

Once the algorithm finds a sample that succeeds in making the face look more memorable without significantly altering the person’s appearance, it makes yet more copies of this new image, with each containing further alterations. It then keeps repeating this process until it finds a version that best meets its objectives.

“It’s really like applying an elastic mesh onto the photograph that slightly modifies the face,” Oliva says. “So the face still looks like you, but maybe with a bit of lifting.”

The team then selected photographs of 500 people and modified them to produce both a memorable and forgettable version of each. When they tested these images on a group of volunteers, they found that the algorithm succeeded in making the faces more or less memorable, as required, in around 75 percent of cases.

Familiarity breeds likability

Making a face appear familiar can also make it seem more likable, Oliva says. She and Bainbridge have published a complementary paper in the Journal of Experimental Psychology: General on the attributes that make a face memorable. The first time we see a face, we tend to “tag” it with attributes based on appearance, such as intelligence, kindness, or coldness. “If we tag a person with familiarity, because we think this is a face we have seen before, we have a tendency to like it more, and for instance to think the person is more trustworthy,” she says.

The team is now investigating the possibility of adding other attributes to their model, so that it could modify faces to be both more memorable and to appear more intelligent or trustworthy, for example. “So you could imagine having a system that would be able to change the features of your face to make you whatever you would wish for, but always in a very subtle way,” Oliva says.

We all wish to use a photo that makes us more visible to our audience, says Aleix Martinez, an associate professor of electrical and computer engineering at Ohio State University. “Painters of the Renaissance knew how to make portraits memorable, but we are clueless on how to take that picture that will give us an edge over others or, at a minimum, show the best side of us,” Martinez says.

Now Oliva and her team have developed a computational algorithm that can do this for us, he says. “Input your preferred picture of your face and it will make it even better,” Martinez says. “This will allow us to gain that advantage we were looking for and hopefully make people remember us more.”

The research was funded by grants from Xerox, Google, Facebook, and the Office of Naval Research.

Jeffrey H. Shapiro has been elected to the grade of Fellow of SPIE, the International Society for Optics and Photonics. SPIE was founded in 1955 to advance light-based technologies. Shapiro, the Julius A. Stratton Professor of Electrical Engineering in the MIT Electrical Engineering and Computer Science Department is also a Fellow of the American Physical Society, the IEEE, the Institute of Physics, and the Optical Society of America. He was Director of the Research Laboratory of Electronics (RLE) at MIT from 2001 to 2011. Shapiro heads (with RLE Senior Research Scientist Franco N.C. Wong) the RLE Optical and Quantum Communications Group, which develops entanglement source and measurement technologies, as well as protocols that use them in photon-efficient communication, imaging and metrology. 

Professor Shapiro is best known for his work on the generation, detection, and applications of squeezed states of light. These are nonclassical light beams whose quadrature components satisfy the Heisenberg uncertainty limit but with unequal variances, thus offering sensitivity improvements in precision measurements made with phase-sensitive (optical homodyne) detection. For this work, he shared the 2008 Quantum Electronics Award from the IEEE Lasers and Electro-Optics Society (now the IEEE Photonics Society). Squeezed-state light is now being employed to enhance the sensitivity of gravity-wave detectors.

Professor Shapiro’s current research focus is on quantum optical communication. Here his most notable accomplishment is his work on quantum illumination for secure communication. In a recent experiment, reported this year in Phys. Rev. Lett., his team demonstrated a quantum illumination protocol — originally described, theoretically, in Prof. Shapiro’s 2009 article in Phys. Rev. A— that is immune to passive eavesdropping. This experiment is also the first time that entanglement has been used to obtain a substantial performance advantage – in this case, six orders of magnitude lower error probability for the intended receiver in comparison with that of the eavesdropper -- over an entanglement-breaking channel.

His most recent work joint with Dr. Vivek Goyal's group and published Nov. 27, 2013 online in Science— demonstrates that high-quality 3D shape and reflectivity images can be obtained from a laser radar that detects only one photon per pixel.

The Spanish Royal Academy of Engineering presented the "Agustin de Betancourt" award to Professor Tomás Palacios on Nov. 26. This award, the most prestigious given in Spain to an engineer less than 36 years old, recognizes Prof. Palacios’ work on nanotechnologies applied to high frequency electronic devices based on GaN and graphene. [Photo: Prof. Palacios posed with Prof. Elias Fereres (left), President of the Spanish Royal Academy of Engineering, and Mr. Rafael del Pino (right), member of the MIT Corporation and CEO of Ferrovial.] 

A member of the MIT faculty and principal investigator at the Microsystems Technology Laboratories (MTL) since 2006, Tomas Palacios focuses on the application of “extreme materials” to electronics. Members of the Palacios Group work on several major projects including applications of the exotic gallium nitride to silicon chips and the use of graphene in large-area transparent electronics that could be layered onto walls, windows or clothes. Palacios http://www-mtl.mit.edu/wpmu/tpalacios/brief-bio-cv/, the Emmanuel E. Landsman Associate Professor of Electrical Engineering and Computer Science, also heads the MIT-MTL Center for Graphene Devices and 2D Systems and the MIT-MTL GaN Center. Read more in the July 2, 2013, MIT News feature on Prof. Palacios.

Prof. Tomás Palacios and several members of his group also received two prestigious awards at the plenary session of the 2013 International Electron Devices Meeting in early December, in Washington DC. IEDM is the premier conference in electron devices and it is a great honor to receive these awards at the plenary session.

At the IEDM, Han Wang, who completed his PhD thesis in June 2013 under Prof. Palacios, received the 2012 Roger A. Haken Best Student Paper Award. The award winning work is titled “Large-Scale 2D Electronics Based Single-Layer MoS2 Grown by Chemical Vapor Deposition.” Dr. Wang also recently received the first prize for the 2013 Jin-Au Kong Doctoral Thesis Prize for Electrical Engineering at MIT.

At the same conference, Bin Lu, Elison Matioli and Tomás Palacios received the 2012 Electron Devices Society George E. Smith Award. This is given to the best article published in IEEE Electron Device Letters in 2012. EDL is a prestigious, fast publication journal where leading research in electron devices is published. The winning paper is titled “Tri-Gate Normally-Off GaN Power MISFET.” Bin Lu was a PhD student with Prof. Palacios and Elison Matioli is a postdoc in the group.

As announced on the Computer Science and Artificial Intelligence website:

December 22, 2013
CSAIL Principal Investigator Srini Devadas and three former students have been selected as the 2014 winners of the Most Influential Paper Award at a prestigious systems research conference.

Devadas, Edward Suh, Jae W. Lee, and David Zhang will be honored at next March’s Nineteenth International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), held in Utah.

The award is given annually to an ASPLOS paper from at least 10 years ago. The CSAIL team’s 2004 paper, “Secure Program Execution Via Dynamic Information Flow Tracking,” proposed a new approach to protecting against malware attacks that provides stronger security for programs that are traditionally more vulnerable. See this paper.

ASPLOS is the premier forum for multidisciplinary systems research spanning computer architecture and hardware, programming languages and compilers, operating systems and networking, as well as applications and user interfaces.

Devadas is the Edwin Sibley Webster Professor of Electrical Engineering and Computer Science at MIT and belongs to the Computation Structures Group. His research interests include computer architecture, computer security, VLSI design, computer-aided design, hardware validation, network router hardware, and computational biology. Read more about Devadas’ work.

Related links:

Electrical Engineering and Computer Science Department graduate student Mohsen Ghaffari, also a member of MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) has developed a new way to use “vertex connectivity” that could ultimately lead to communication protocols that will allow as much network bandwidth as possible. Ghaffari and members of an international team will present this work in January at the ACM-SIAM Symposium on Discrete Algorithms in Portland, Oregon.

Read more in the Dec. 24, 2013 MIT News Office article by MIT News correspondent Helen Knight titled “New approach to vertex connectivity could maximize networks’ bandwidth – Technique advances understanding of a basic concept in graph theory, paralleling advances in edge connectivity,” also posted below.

Computer scientists are constantly searching for ways to squeeze ever more bandwidth from communications networks.

Now a new approach to understanding a basic concept in graph theory, known as “vertex connectivity,” could ultimately lead to communications protocols — the rules that govern how digital messages are exchanged — that coax as much bandwidth as possible from networks.

Graph theory plays a central role in mathematics and computer science, and is used to describe the relationship between different objects. Each graph consists of a number of nodes, or vertices, which represent the objects, and connecting lines between them, known as edges, which signify the relationships between them. A communications network, for example, can be represented as a graph with each node in the network being one vertex, and a connection between two nodes depicted as an edge.

One of the fundamental concepts within graph theory is connectivity, which has two variants: edge connectivity and vertex connectivity. These are numbers that determine how many lines or nodes would have to be removed from a given graph to disconnect it. The lower the edge-connectivity or vertex-connectivity number of a graph, therefore, the easier it is to disconnect, or break apart.

In this way both concepts show how robust a network is against failure, and how much flow can pass through it — whether the flow of information in a communications network, traffic flow in a transportation system, or fluid flow in hydraulics.

Reducing edge connectivity’s edge

However, while a great deal of research has been carried out in mathematics to solve problems associated with edge connectivity, there has been relatively little success in answering questions about vertex connectivity.

But at the ACM-SIAM Symposium on Discrete Algorithms in Portland, Ore., in January, Mohsen Ghaffari, a graduate student in the Computer Science and Artificial Intelligence Laboratory at MIT, will present a new technique for addressing vertex-connectivity problems.

“This could ultimately help us understand how to build more robust and faster networks,” says Ghaffari, who developed the new approach alongside Keren Censor-Hillel at the Technion and Fabian Kuhn at the University of Freiburg.

In the 1960s, mathematicians William Tutte and Crispin Nash-Williams separately developed theories about structures called edge-disjoint spanning trees, which now serve as one of the key technical tools in many problems about edge connectivity.

A spanning tree is a subgraph — or a graph-within-a-graph — in which all of the nodes are connected by the smallest number of edges. A set of spanning trees within a graph are called “edge-disjoint” if they do not share any of these connecting lines.

If a network contains three edge-disjoint spanning trees, for example, information can flow in parallel along each of these trees at the same time, meaning three times more bandwidth than would be possible in a graph containing just one tree. The higher the number of edge-disjoint spanning trees, the larger the information flow, Ghaffari says. “The results of Tutte and Nash-Williams show that each graph contains almost as many spanning trees as its edge connectivity,” he says.

Now the team has created an analogous theory about vertex connectivity. They did this by breaking down the graph into separated groups of nodes, known as connected dominating sets. In graph theory, a group of nodes is called a connected dominating set if all of the vertices within it are connected to one another, and any other node within the graph is adjacent to at least one of those inside the group.

In this way, information can be disseminated among the nodes of the set, and then passed to any other node in the network.

So, in a similar way to Tutte and Nash-Williams’ results for edge connectivity, “each graph contains almost as many vertex-disjoint connected dominating sets as its vertex connectivity,” Ghaffari says.

“So if you think of an application like broadcasting information through a network, we can now decompose the network into many groups, each being one connected dominating set,” he says. “Each of these groups is then going to be responsible for broadcasting some set of the messages, and all groups work in parallel to broadcast all the messages fast — almost as fast as possible.”

The team has now developed an algorithm that can carefully decompose a network into many connected dominating sets. In this way, it can structure so-called wireless ad hoc networks, in which individual nodes route data by passing it from one to the next to ensure the best possible speed of information flow. “We want to be able to spread as much information as possible per unit of time, to create faster and faster networks,” Ghaffari says. “And when a graph has a better vertex connectivity, it allows a larger flow [of information],” he adds.

Applications in assessing robustness

The researchers can also use their new approach to analyze the robustness of a network against random failures. “These new techniques also allow us to analyze whether a network is likely to remain connected when its nodes fail randomly with some given probability,” Ghaffari says. “Reliability against random edge failures is well understood, but we knew much less about that against node failures,” he adds.

Noga Alon, a professor of mathematics and computer science at Tel Aviv University, says Ghaffari and his fellow authors have identified the notion that determines the largest achievable flow when broadcasting messages using routing in communication networks.

“The investigation of this notion, vertex disjoint connected dominating sets, is treated in this paper by an elegant combination of combinatorial, probabilistic, and algorithmic techniques,” he says.

A member of the MIT faculty since 1967, Roberge spent nearly his entire professional career at MIT.

James K. Roberge, professor of electrical engineering in the Department of Electrical Engineering and Computer Science (EECS) since 1967, died Friday, Jan. 10, 2014. Roberge continued teaching in the department through the fall 2013 term. 

Born in Jersey City, New Jersey in 1938, Jim Roberge came to MIT in 1956, earning the SB, SM and ScD degrees, all in electrical engineering. For nearly all of his professional career, Jim worked for MIT – from postdoctoral research associate to full professor. Since 1969, Jim performed research at Lincoln Laboratory.

His research interests in the area of electronic circuits and systems design led him to work in a division at Lincoln Laboratory involved in space communications, instrumentation, and optical communications. His designs have flown on nine satellites.

EECS colleague Vincent Chan, the Joan and Irwin Jacobs Professor of Electrical Engineering and Computer Science, headed the division at Lincoln Lab in which Jim worked. Chan notes that Roberge’s two most important contributions are ultra-high-efficiency power converters for spacecraft and high-precision optical tracking electronics for space laser communications.

“[Jim] brought together his knowledge of circuit designs, control system theory and a large dose of ingenuity to design these systems,” Chan notes. Despite the fact that some of his work was done in the 1980s and 1990s, Chan says, “it [Roberge’s work] still represents the state of the art.”

James Roberge is noted by the colleagues he worked with over the years for his mentorship to not only students but to newer faculty just beginning their careers at MIT. Charlie Sodini, the LeBel Professor of Electrical Engineering and member of the MIT EECS faculty since 1983, notes about Jim’s influence on him: “I taught 6.301, [Solid-State Circuits] and 6.302, Feedback Systems, as a recitation instructor for Jim. It was a pleasure to learn the material from someone who had it in his DNA.”

Prof. Roberge is also revered for his teaching and mentoring – encouraging a number of students who are now following in his academic and research footprints. David Trumper, faculty member of the MIT Mechanical Engineering Department since 1993, began his association with Prof. Roberge as an undergraduate student taking 6.301 and 6.302 – classes, which he says “opened up analog circuits as a design discipline.” Roberge served as David Trumper’s undergraduate thesis advisor and later (1987-90) his PhD advisor. Trumper says all will remember Jim for his “keen insights and easy confidence that pretty much any problem could be solved if you looked at it from the right perspective.”

Kent Lundberg, who was a student with Prof. Roberge while he earned his SM and PhD in electrical engineering, is currently a Visiting Professor at Olin College of Engineering. Having taught 6.331 with Prof. Roberge since 1994 and having taught with him this past term (fall 2013), Lundberg says “Knowing Professor Roberge was the best part of my education at MIT.”

Through his research and eye for practical application, Jim Roberge authored 12 patents and worked with more than 160 consulting clients. He was co-founder of Hybrid Systems Corporation, later acquired by Sprague, and of Aerogage Corporation.

Prof. Roberge authored several books including “Operational Amplifiers: Theory and Practice” – a text that has been widely recognized as the authoritative classic. His lectures on Electronic Feedback Systems are available at http://ocw.mit.edu/resources/res-6-010-electronic-feedback-systems-spring-2013/index.htm. This website also includes a pdf copy of his textbook, along with a course manual. Also see the Teaching Excellence at MIT videos series on teaching excellence: James K. Roberge 6.302 (Electronic Feedback Systems).

An avid model trains hobbyist,Jim Roberge created a final lecture for 6.302 to demonstrate the classic idea in feedback that – in his words – “something you want to control comes at least in good part from measurement.” Using a 1990 Lionel model with speed control, Jim was pleased to incorporate most of the feedback principles from the entire class in this demo. See the May 13, 2010, Train Lecture video.

EECS Department Head Anantha Chandrakasan summarized Jim Roberge’s impact in his announcement to his colleagues saying: “Jim was a wonderful colleague, teacher, researcher and mentor. He was legendary for his teaching of analog circuits (6.002, 6.301, 6.302, 6.331) and his approach to these subjects had a profound influence on generations of students.”

Jim Roberge is survived by his wife Nancy J. Roberge, his son James D. Roberge and his daughter Anne E. Roberge. A funeral service will be held Tuesday, Jan. 14 at the Douglass Funeral Home, 51 Worthen Road, Lexington at 10 AM. Visiting hours will be held Monday, Jan. 13 from 5 to 8pm. Donations in James K. Roberge’s memory may be made to the MIT Scholarship Fund, 600 Memorial Drive, Cambridge, MA 02139.

Marvin Minsky, a faculty member in the MIT Electrical Engineering and Computer Science since 1958 and co-founder (in 1959) of the Artificial Intelligence Lab (now the Computer Science and Artificial Intelligence Laboratory), has been recognized the the BBVA Foundation for his lifetime achievements in establishing the field of artificial intelligence as well as his contributions to mathematics, cognitive science, robotics and philosophthy.

Read more in the Jan. 17, 2014 MIT News Office article by Ellen Hoffman, Media Lab titled "Marvin Minsky honored for lifetime achievements in artificial intelligence - The MIT professor emeritus earns the BBVA Foundation Frontiers of Knowledge Award for his pioneering work and mentoring role in the field of artificial intelligence," also posted below in its entirety.

MIT Media Lab professor emeritus Marvin Minsky, 86, a pioneer in the field of artificial intelligence, has won the BBVA Foundation Frontiers of Knowledge Award in the information and communications technologies category.

The BBVA Foundation cited his influential role in defining the field of artificial intelligence, and in mentoring many of the leading minds in today’s artificial intelligence community. The award also recognizes his contributions to the fields of mathematics, cognitive science, robotics, and philosophy.

In learning of the award, which brings a prize of $540,000, Minsky reconfirmed his conviction that one day we will develop machines that will be as smart as humans. But he added “how long this takes will depend on how many people we have working on the right problems. Right now there is a shortage of both researchers and funding.”

Minsky joined the Department of Electrical Engineering and Computer Science faculty in 1958, and co-founded the Artificial Intelligence Laboratory (now the Computer Science and Artificial Intelligence Laboratory) the following year. In 1985, he became a founding member of the Media Lab, where he was named the Toshiba Professor of Media Arts and Sciences, and where he continues to teach and mentor.

Commenting on the award, Nicholas Negroponte, co-founder and chairman emeritus of the Media Lab, says, “Marvin’s genius is accompanied by extreme kindness and humor. He listens well, and is oracle-like in his capability to debug an enormously complex situation with a simple, short phrase. Through the 47 years we have known each other, he has taught me to tackle the big problems.”

Patrick Winston, the Ford Professor of Artificial Intelligence and Computer Science and former director of MIT’s Artificial Intelligence Lab, says, “One day, when I was wondering what I wanted to do, I went to one of Marvin's lectures, invited by a friend. At the end, I said to myself, I want to do what he does. And ever since, that is what I have done.”

Minsky views the brain as a machine whose functioning can be studied and replicated in a computer, which would teach us, in turn, to better understand the human brain and higher-level mental functions. He has been recognized for his work focusing on how we might endow machines with common sense — the knowledge humans acquire every day through experience. How, for example, do we teach a sophisticated computer that to drag an object on a string, you need to pull not push — a concept easily mastered by a two-year-old child.

Minsky’s book, “The Society of Mind” (1985) is considered the seminal work on exploring intellectual structure and function, and for understanding the diversity of the mechanisms interacting in intelligence and thought. Other achievements include building the first neural network simulator (SNARC), as well as mechanical hands and other robotic devices. Minsky is the inventor of the earliest confocal scanning microscope. He was also involved in the inventions of the first "turtle," or cursor, for the LOGO programming language (with Seymour Papert), and the "Muse" synthesizer for musical variations (with Ed Fredkin). His most recent book, “The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind,” was published in 2006.

Minsky has received numerous awards, among them the ACM Turing Award, the Japan Prize, the Royal Society of Medicine Rank Prize (for Optoelectronics) and the Optical Society (OSA) R.W. Wood Prize.

Minsky graduated from Harvard University in 1950, and received his PhD from Princeton University in 1954. He was appointed a Harvard University Junior Fellow from 1954 to 1957.

The BBVA Foundation was established by the BBVA Group, a global financial service group based in Spain. The Frontiers of Knowledge Awards, established in 2008, honor achievements in the arts, science, and technology. They focus on contributions of lasting impact for their originality, theoretical significance and ability to push back the frontiers of the known world.

Scenes from Start6, the EECS Workshop for entrepreneurs and innovators, Jan. 13 - 28, 2014. Photos by Rahul Rithe, EECS graduate student. Captions below. More information? see the Start6 website

Written by Lauren J. Clark

In Start6, a new entrepreneurship program for MIT engineering students offered during IAP, participants have received advice from such guest speakers as Paul English, cofounder of Kayak; Mike Evans’99, MEng ’00, and COO and cofounder of GrubHub; Marina Hatsopoulos’92, serial entrepreneur, former CEO and director of Z Corporation, and angel investor; and Max Krohn’08, cofounder of OkCupid. And that was just on the first day.

The three-week workshop, which began Jan. 13, also features visits from Drew Houston’05, CEO and cofounder of Dropbox; Google vice president Jeremy Wertheimer’89, former CEO of ITA Software; Nanxi Liu, a 23-year-old who has already founded two successful startups; Rodney Brooks, founder, chairman, and CTO of Rethink Robotics and Panasonic Professor of Robotics (emeritus) at MIT; Ray Stata’57, cofounder of Analog Devices; and Robert Langer, prolific inventor and entrepreneur and the David H. Koch Institute Professor at MIT. In addition, venture capitalists Peter Levine of Andreessen Horowitz and Jamie Goldstein’89 of North Bridge Venture Partners walked the Start6 students through the various phases of a startup.

Learning from the Pros

“It’s awesome to be able to hear insightful things from people who have done this before and know what they’re talking about,” says Ari Weinstein, a freshman from Philadelphia who plans to major in electrical engineering and computer science (EECS) and already has some entrepreneurial experience. He created DeskConnect, an app that allows users to share files between devices with one button. DeskConnect already has more than 100,000 users.

“MIT has excellent resources for aspiring entrepreneurs,” says Ian A. Waitz, dean of the School of Engineering. “Our students, faculty, staff, and alumni have an exceptional track record of producing successful new ventures. However, increasingly our students see the acquisition of entrepreneurial knowledge, skills, and attitudes — whether for use in starting a new venture or in an existing organization — as an essential part of their education. Start6 is one of several exciting new initiatives that will provide even greater opportunities for our students to develop these essential abilities.”

The 50-plus students participating in the workshop are primarily from, but not limited to, EECS.

Anantha Chandrakasan, EECS department head and Joseph F. and Nancy P. Keithley Professor of Electrical Engineering, says that Start6 is a new opportunity for MIT's engineering students and postdoctoral candidates to dive into “everything entrepreneurship — particularly as it relates to EECS.” He told the workshop attendees: "Our ultimate goal is to create a community of entrepreneurs, not just at MIT, but when you go out into the world."

Evans of the online food-ordering company GrubHub gave a talk chronicling his journey from being a young corporate employee paying off student debt in 2003 to being the COO of a company that did $1 billion in sales last year. GrubHub, which recently merged with competitor Seamless, covers 20,000 restaurants in about 500 cities.

Intellectual Capital 

“In the past, you needed a massive amount of capital to start a company,” Evans said. “The people in this room have the capital in their minds — in their ability to write software. You can go create businesses with very little capital.”

Start6 offers practical sessions that help students with the nuts and bolts of a startup, such as how to perfect a product pitch; how to fund a company, all the way from bootstrapping (relying on support from yourself, family, and friends) to venture capital; and how to split equity among company founders. Students say that they appreciate both the how-to aspect of the workshop and the stories of successful entrepreneurs — stories in which several themes emerge again and again: passion, focus, persistence, resilience, and team-building.

“Be passionate about your idea,” said Dave Gifford, EECS professor and founder of three successful companies. “A startup has to be meaningful to you as a creative act. Money is secondary.”

Hatsopoulos, former CEO and director of 3-D printing leader Z Corporation, stressed the importance of building the right team to lead a startup. "Each member should bring something very unique to the table. Then this team can do magic — it can create something that’s so much bigger than any one of you."

Persistence to ride out the tough times is key, said Rob May, CEO and cofounder of Backupify, which securely backs up data in the cloud. "Do you have the stomach for a startup? In the early days, it’s often only the will of the founder that keeps people there.”

Paul English urged the students to boil their idea for a startup down to a simple idea or a narrow market. When he started the travel website Kayak a decade ago, he pitched it simply as “the anti-Expedia.” He learned to avoid explaining all of the site’s features, or the algorithms that made it work, to potential funders or buyers. Its success has been such that Priceline purchased it for nearly $2 billion last year.

“Engineers tend to be pretty cerebral,” English says. “For every problem presented to us, we try to come up with solutions that solve 10 additional problems. We need to be more decisive.”

That message resonated with Sam Prentice, an EECS graduate student. “It’s very easy here at MIT to get focused on the technology instead of building something that someone wants,” he says. He has several ideas for startups, including one based on a technology that augments human perception.

“What I’ve learned has already transformed my project,” says EECS senior Danielle Gordon. Her software, called Mode, enables users to link together disparate data, such as social media accounts and files stored on one’s computer. Before Start6, she says, she had been describing the technology as a “way to link objects together for organization purposes. Now I’m calling it a content management system for life.”

When to start a company?

One topic that comes up frequently in Start6 panel discussions is when to start a company. Nanxi Liu answers unequivocally: “I recommend students start a company as soon as they can, and especially while they are still students. They’ve got tons of student organizations that they can send beta codes out to for testing their product.”

Liu, a graduate of the University of California at Berkeley, is CEO of the year-old startup Enplug, which has placed its interactive digital billboards — on which advertising and social media blend in real time — in more than 30 cities. Before that, she founded Nanoly Bioscience, which is developing a chemical that allows vaccines to survive without refrigeration.

She told the students that starting a company early means that “by the time you graduate, you'll be able to hit the ground running on a full-time startup without making any rookie mistakes.”

Just as Evans reminded Start6 participants that they have the capital “in their minds” to start a company, Liu pointed out another readily available resource: fellow students. “In the real world,” she said, “companies pay tens of thousands of dollars to recruiting firms to help them get connected with students at MIT. So, for students at MIT, getting classmates and acquaintances to be teammates is a recruiting jackpot.”

For more information see the Start6 website: http://start6.mit.edu.

Slideshow photo captions. [Photos taken by EECS graduate student Rahul Rithe]

1. Start6 banner
2. Mike Evans, ’99, MEng ’00, and COO and cofounder of GrubHub discussed the life cycle of a start-up.
3. Marina Hatsopoulos, Director DearKate, discussed the A to Z of a startup.
4. Day 1 Panel moderated by Christina Chase, MIT Entrepreneur in Residence, Martin Trust Center discussed Why Startups Fail. Panelists: Max Krohn, Co-Founder, OkCupid; Rob May, CEO and Copfounder, Bakupify; David Gifford, EECS professor of computer science and engineering; Saman Amarasinghe, EECS professor of computer science and engineering.
5. Rodney Brooks Founder, Chairman and CTO of Rethink Robotics (formerly Heartland Robotics), talked about customer buy-in.
6. Jamie Goldstein, '89, General Partner with North Bridge Partners engaged members of the class on some of the fine points of equity distribution. Goldstein said: "Start6 is a fabulous way for to any student interested in innovation to learn about entrepreneurship. This is a great new resource on campus and will result in many students finding their way to building the next generation of important MIT companies."
7. Jeremy Wertheimer, VP, Google (formerly CEO, ITA Software), led a discussion about building what people want.
8. Susie Riley, Founder, Aquto (top left), led a panel including Jinane Abounadi (top, center), Global Head, Regional Products, Travelport; Scott Weller (top right), Co-Founder, CTO, Session M; and Matthew Bellows (lower row), Founder and CEO, Yesware.
9. MIT's Associate Dean for Innovation, Fiona Murray talked about making innovation and entrepreneurship an integral part of MIT's educational program.
10. Raymie Stata (left) CEO, Altiscale discussed go-to-market strategies and his father Ray Stata (right) '57, Co-founder, Analog Devices, Inc., discussed management and team building.
11. Peter Levine, venture capitalist with Andreessen Horowitz (A16Z) spoke about how character affects an organization. Reflecting on his participation in several Start6 sessions, Levine commented: "Engaging with MIT students who are budding entrepreneurs couldn't be more energizing. The Start6 students are awesome! I have no doubt that there will be some strong startups that ultimately stem from this experience."
12. Panel on Marketing & PR Strategies moderated by Christina Chase (top left) included (clockwise, from top middle) Erica Swallow, founder, Deliverish; Elaine Chen, senior lecturer, MIT Sloan School of Management; Kris Bronner, MIT freshman and Co-Creator, UNREAL Brands; Cory von Wallenstein, CTO, Dyn; and marketing specialist Giuseppe Frustaci.
13. Allison Yost, Managing Director of MIT's 100K Challenge led a discussion about navigating the 100K Challenge with Matt Verminski, VP of Hardware, Kiva Systems and Andrea Colaco, PhD candidate at the MIT Media Lab and research affiliate in the MIT Research Lab of Electronics, Founder of 3dim, winner of 100K competition 2013.
14. Ash Ashutosh, Founder and CEO, Actifio, spoke about equity division, considered one of the most difficult elements of starting a company. Here he talked with interested students following his talk.
15. Start6 panel on Company Formation, Culture and Hiring, moderated by Michael Skok, General Partner, North Bridge Venture Partners (top left photo) including (photo center) Erika Angle, CEO, Co-founder, Counterpoint Health Solutions; (top right) Roger Marino, Co-founder EMC; (lower right) Elias Torres, VP of Engineering, Hubspot; and (lower left) Rene Reinsberg, GM/VP Product, GoDaddy, former CEO/Co-Founder at Locu.
16. Nanxi Liu, Founder and CEO, Enplug, discussed building a team.
17. Funding Strategies panel moderated by Siva Narendra, (top left) Co-Founder, CEO of Tyfone, Inc. Members of the panel (clockwise from top right) included Arthur Fox, Creator of Royalty-based investment methodology; Director Eureka Partners I, LLC; Bril Flint, (lower left) Supply Chain Officer, Neogenis Labs; Kush Gulati (bottom, center) Co-Founder, Cambridge Analog Technologies, CAT; and Stan Reiss, Partner, Matrix Partners.