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Integrating optical components into existing chip designs

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New technique enables use of more modern transistor technologies. Image: Amir Atabaki

Two and a half years ago, a team of researchers led by groups at MIT, the University of California at Berkeley, and Boston University announced a milestone: the fabrication of a working microprocessor, built using only existing manufacturing processes, that integrated electronic and optical components on the same chip.

The researchers’ approach, however, required that the chip’s electrical components be built from the same layer of silicon as its optical components. That meant relying on an older chip technology in which the silicon layers for the electronics were thick enough for optics.

In the latest issue of Nature, a team of 18 researchers, led by the same MIT, Berkeley, and BU groups, reports another breakthrough: a technique for assembling on-chip optics and electronic separately, which enables the use of more modern transistor technologies. Again, the technique requires only existing manufacturing processes.

“The most promising thing about this work is that you can optimize your photonics independently from your electronics,” says Amir Atabaki, a research scientist at MIT’s Research Laboratory of Electronics and one of three first authors on the new paper. “We have different silicon electronic technologies, and if we can just add photonics to them, it’d be a great capability for future communications and computing chips. For example, now we could imagine a microprocessor manufacturer or a GPU manufacturer like Intel or Nvidia saying, ‘This is very nice. We can now have photonic input and output for our microprocessor or GPU.’ And they don’t have to change much in their process to get the performance boost of on-chip optics.”

Light appeal

Moving from electrical communication to optical communication is attractive to chip manufacturers because it could significantly increase chips’ speed and reduce power consumption, an advantage that will grow in importance as chips’ transistor count continues to rise: The Semiconductor Industry Association has estimated that at current rates of increase, computers’ energy requirements will exceed the world’s total power output by 2040.

The integration of optical — or “photonic” — and electronic components on the same chip reduces power consumption still further. Optical communications devices are on the market today, but they consume too much power and generate too much heat to be integrated into an electronic chip such as a microprocessor. A commercial modulator — the device that encodes digital information onto a light signal — consumes between 10 and 100 times as much power as the modulators built into the researchers’ new chip.

It also takes up 10 to 20 times as much chip space. That’s because the integration of electronics and photonics on the same chip enables Atabaki and his colleagues to use a more space-efficient modulator design, based on a photonic device called a ring resonator.

“We have access to photonic architectures that you can’t normally use without integrated electronics,” Atabaki explains. “For example, today there is no commercial optical transceiver that uses optical resonators, because you need considerable electronics capability to control and stabilize that resonator.”

Atabaki’s co-first-authors on the Nature paper are Sajjad Moazeni, a PhD student at Berkeley, and Fabio Pavanello, who was a postdoc at the University of Colorado at Boulder, when the work was done. The senior authors are Rajeev Ram, a professor of electrical engineering and computer science at MIT; Vladimir Stojanovic, an associate professor of electrical engineering and computer sciences at Berkeley; and Milos Popovic, an assistant professor of electrical and computer engineering at Boston University. They’re joined by 12 other researchers at MIT, Berkeley, Boston University, the University of Colorado, the State University of New York at Albany, and Ayar Labs, an integrated-photonics startup that Ram, Stojanovic, and Popovic helped found.

Sizing crystals

In addition to millions of transistors for executing computations, the researchers’ new chip includes all the components necessary for optical communication: modulators; waveguides, which steer light across the chip; resonators, which separate out different wavelengths of light, each of which can carry different data; and photodetectors, which translate incoming light signals back into electrical signals.

Silicon — which is the basis of most modern computer chips — must be fabricated on top of a layer of glass to yield useful optical components. The difference between the refractive indices of the silicon and the glass — the degrees to which the materials bend light — is what confines light to the silicon optical components.

The earlier work on integrated photonics, which was also led by Ram, Stojanovic, and Popovic, involved a process called wafer bonding, in which a single, large crystal of silicon is fused to a layer of glass deposited atop a separate chip. The new work, in enabling the direct deposition of silicon — with varying thickness — on top of glass, must make do with so-called polysilicon, which consists of many small crystals of silicon.

Single-crystal silicon is useful for both optics and electronics, but in polysilicon, there’s a tradeoff between optical and electrical efficiency. Large-crystal polysilicon is efficient at conducting electricity, but the large crystals tend to scatter light, lowering the optical efficiency. Small-crystal polysilicon scatters light less, but it’s not as good a conductor.

Using the manufacturing facilities at SUNY-Albany’s Colleges for Nanoscale Sciences and Engineering, the researchers tried out a series of recipes for polysilicon deposition, varying the type of raw silicon used, processing temperatures and times, until they found one that offered a good tradeoff between electronic and optical properties.

“I think we must have gone through more than 50 silicon wafers before finding a material that was just right,” Atabaki says.

For related information, visit the MIT News website.

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Thursday, April 19, 2018 - 7:30am

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A new way to automatically build road maps from aerial images

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Image: Courtesy of the researchers

Adam Conner-Simons | CSAIL

Map apps may have changed our world, but they still haven’t mapped all of it yet. Specifically, mapping roads can be difficult and tedious: Even after taking aerial images, companies still have to spend many hours manually tracing out roads. As a result, even companies like Google haven’t yet gotten around to mapping the vast majority of the more than 20 million miles of roads across the globe.

Gaps in maps are a problem, particularly for systems being developed for self-driving cars. To address the issue, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have created RoadTracer, an automated method to build road maps that’s 45 percent more accurate than existing approaches.

sing data from aerial images, the team says that RoadTracer is not just more accurate, but more cost-effective than current approaches. Mohammad Alizadeh, an assistant professor in EECS, says this work will be useful both for tech giants like Google and for smaller organizations without the resources to curate and correct large amounts of errors in maps.  

“RoadTracer is well-suited to map areas of the world where maps are frequently out of date, which includes both places with lower population and areas where there’s frequent construction,” says Alizadeh, one of the co-authors of a new paper about the system. “For example, existing maps for remote areas like rural Thailand are missing many roads. RoadTracer could help make them more accurate.”

For example, looking at aerial images of New York City, RoadTracer could correctly map 44 percent of its road junctions, which is more than twice as effective as traditional approaches based on image segmentation that could map only 19 percent.

The paper, which will be presented in June at the Conference on Computer Vision and Pattern Recognition (CVPR) in Salt Lake City, Utah, is a collaboration between CSAIL and the Qatar Computing Research Institute (QCRI).

Alizadeh’s MIT co-authors include graduate students Fayven Bastani and Songtao He, and three EECS/CSAIL colleagues: Hari Balakrishnan, the Fujitsu Professor in EECS; Professor Sam Madden; and Adjunct Professor David DeWitt. QCRI co-authors include senior software engineer Sofiane Abbar and Sanjay Chawla, who is the research director of QCRI’s Data Analytics Group.

Current efforts to automate maps involve training neural networks to look at aerial images and identify individual pixels as either “road” or “not road.” Because aerial images can often be ambiguous and incomplete, such systems also require a post-processing step that’s aimed at trying to fill in some of the gaps.

Unfortunately, these so-called “segmentation” approaches are often imprecise: If the model mislabels a pixel, that error will get amplified in the final road map. Errors are particularly likely if the aerial images have trees, buildings, or shadows that obscure where roads begin and end. (The post-processing step also requires making decisions based on assumptions that may not always hold up, like connecting two road segments simply because they are next to each other.)

Meanwhile, RoadTracer creates maps step-by-step. It starts at a known location on the road network, and uses a neural network to examine the surrounding area to determine which point is most likely to be the next part on the road. It then adds that point and repeats the process to gradually trace out the road network one step at a time.

“Rather than making thousands of different decisions at once about whether various pixels represent parts of a road, RoadTracer focuses on the simpler problem of figuring out which direction to follow when starting from a particular spot that we know is a road,” says Bastani. “This is in many ways actually a lot closer to how we as humans construct mental models of the world around us.”

The team trained RoadTracer on aerial images of 25 cities across six countries in North America and Europe, and then evaluated its mapping abilities on 15 other cities.

“It’s important for a mapping system to be able to perform well on cities it hasn’t trained on, because regions where automatic mapping holds the most promise are ones where existing maps are non-existent or inaccurate,” says Balakrishnan.

Bastani says that the fact that RoadTracer had an error rate that is 45 percent lower is essential to making automatic mapping systems more practical for companies like Google.

“If the error rate is too high, then it is more efficient to map the roads manually from scratch versus removing incorrect segments from the inferred map,” says Bastani.

Still, implementing something like RoadTracer wouldn’t take people completely out of the loop: The team says that they could imagine the system proposing road maps for a large region and then having a human expert come in to double-check the design.

“That said, what’s clear is that with a system like ours you could dramatically decrease the amount of tedious work that humans would have to do,” Alizadeh says.

Indeed, one advantage to RoadTracer’s incremental approach is that it makes it much easier to correct errors; human supervisors can simply correct them and re-run the algorithm from where they left off, rather than continue to use imprecise information that trickles down to other parts of the map.

Of course, aerial images are just one piece of the puzzle. They don’t give you information about roads that have overpasses and underpasses, since those are impossible to ascertain from above. As a result, the team is also separately developing algorithms that can create maps from GPS data, and working to merge these approaches into a single system for mapping.

This project was supported, in part, by the Qatar Computing Research Institute.

For additional content and a video, visit the MIT News website.

Date Posted: 

Tuesday, April 17, 2018 - 8:30am

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The 'RoadTracer' system from the Computer Science and Artificial Intelligence Laboratory could reduce workload for developers of apps like Google Maps.

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Two from EECS are among three MIT graduate students to receive Soros Fellowships

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L to R: Sitan Chen, Lilly Chin '17, Suchita Nety. Illustration: MIT News Office

Two EECS graduate students, Sitan Chen and Lillian Chin '17, are among the 30 recipients of the 2018 Paul and Daisy Soros Fellowships for New Americans. They're joined by Suchita Nety, who is working toward an MD/PhD from MIT and Harvard.

In addition, Sylvia Biscoveanu, a recent graduate of Penn State University who will be pursuing a PhD at the MIT Kavli Institute for Astrophysics and Space Research next fall, was also named a Soros Fellow.

The fellowships provide up to $90,000 funding for graduate studies for immigrants and the children of immigrants. Award winners are selected for their potential to make significant contributions to United States society, culture, or their academic fields. This year, over 1,700 candidates applied to the prestigious fellowship program.

In the past eight years, 29 MIT students and alumni have been awarded Soros Fellowships. Eligible applicants include children of immigrants, naturalized citizens, green card holders, and Deferred Action for Childhood Arrival (DACA) recipients. Beginning in 2019, the fellowship will expand its requirements to include former DACA recipients should the government program be rescinded.

MIT students interested in applying to the Soros Fellowship should contact Kim Benard, assistant dean of distinguished fellowships and academic excellence. The application for the Soros Class of 2019 is now open, and the national deadline is Nov. 1, 2018. 

Sitan Chen

Sitan Chen is a PhD student in electrical engineering and computer science and a member of the MIT Computer Science and Artificial Intelligence Lab (CSAIL) and the Theory of Computation Group. Chen's award will support work toward his doctorate in computer science.

Born in Hefei, China, Chen was just a year old when his family immigrated to Canada so that his father could complete his doctorate at the University of Toronto. The family moved to Suwanee, Georgia, in the early 2000s, and Chen’s experiences throughout high school with math contests and programs like the Research Science Institute ultimately motivated him to study mathematics and computer science at Harvard University.

Chen graduated summa cum laude from Harvard in 2016, receiving the Thomas T. Hoopes and Captain Jonathan Fay Prizes for his thesis on geometric aspects of counting complexity and arithmetic complexity. Chen’s mentors in Harvard's Theory of Computing research group encouraged him to pursue graduate studies in theoretical computer science.

In the fall of 2016, Sitan began his doctoral program in computer science at MIT. His work with PhD advisor Ankur Moitra, professor in the Department of Mathematics and principal investigator at CSAIL, centers on algorithmic problems in machine learning and inference.

Chen is focusing on developing new mathematical frameworks to analyze techniques such as the method of moments, Gibbs sampling, and local search that are popular in practice but poorly understood in theory. He has presented his work at venues including the Symposium on Theory of Computing and the Simons Institute for the Theory of Computing.

Lillian Chin '17

Lillian Chin graduated from MIT in June 2017 with a bachelor of science degree in electrical engineering and computer science. She continued on to a doctoral program in the department, and her award will support work toward a PhD in electrical engineering and computer science. As a graduate student at MIT, her research interests are in robotics — specifically, integrating versatile hardware design with strong control algorithms.

Chin was born in New York City after her parents left China and Taiwan to pursue graduate school in the United States. Her parents instilled Chin’s love of science by frequently taking her to their lab and explaining their experiments. As she grew older, Chin began pursuing engineering and research more intensely, competing on an international level in the FIRST Robotics Competition and being nationally recognized for bioengineering research through the Intel Science Talent Search.

During her undergraduate career at MIT, Chin further developed her skills in strong interdisciplinary research, creating new materials that could be used to more efficiently move soft robots, and designing a novel manufacturing process that can print tissues and circuits. Chin also was able to pursue summer internships at Apple, Square, and the Toyota Research Institute. And in February 2017, Chin bested thousands of applicants and 14 on-air competitors when she won the 2017 "Jeopardy!" College Championship, representing MIT.

As a graduate student at MIT and a 2018 Hertz Fellow, Chin is currently working on better integrating the mechanical advantages of soft robotics with the latest in learning and planning algorithms. Her ultimate career goal is to become a professor in robotics: designing systems to enable human achievement.

For more information, visit the MIT News website.

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Tuesday, April 17, 2018 - 8:45am

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Summit explores pioneering approaches for AI and digital technologies for health care

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Summit speakers included (L to R) Jay Bradner of the Novartis Institute for BioMedical Research; MIT Institute Professor Phillip Sharp; Andrew Plump of Takeda; summit organizers and EECS Professors Regina Barzilay and Dina Katabi; MIT President Emerita Susan Hockfield; and Robert Califf of Duke University. Photo: Lillie Paquette/School of Engineering.

Meg Murphy | School of Engineering

 

MIT EECS professors and MacArthur Fellows Regina Barzilay and Dina Katabi recently gathered leaders in technology, biotech, and regulatory agencies for a summit to inspire widespread adoption of artificial intelligence and digital technologies in health care. 

MIT is surrounded by pharmaceutical companies, but until now there has been sparse connection between AI research at MIT and research on drug discovery. The fields have in essence spoken different languages and existed worlds apart.

Barzilay and Katabi are set to change that. Less than a year ago, they started a collaboration with pharmaceutical companies and quickly recognized a wealth of new research questions and an opportunity to transform the process of drug design and manufacturing.

“When Dina and I thought to organize this symposium, we wanted to bring these two communities together, and identify hard questions MIT and pharma can solve together,” said Barzilay, the Delta Electronics Professor in EECS.

She and Katabi, the Andrew and Erna Viterbi Professor in EECS, attracted 120 participants from 15 pharmaceutical companies, the U.S. Food and Drug Administration (FDA), area hospitals, and MIT colleagues in electrical engineering, computer science, biology, and business to the summit.

Bringing digital health to translational medicine

The morning kicked off with a welcome from Phillip Sharp, an MIT Institute Professor, professor of biology, and member of the Koch Institute for Integrative Cancer Research, who introduced keynote speaker Jay Bradner, the president of the Novartis Institute for BioMedical Research. Machine learning represents a “new wave to surf on” for the field of biomedicine, said Bradner.

“We so desperately need your help because this science has real challenges,” said Bradner, who leads 6,000 scientists located all over the world. Among them, he said, “150 are data scientists — and that’s not enough.” He ended his keynote with: “I know that together we can totally reimagine medicine.”

Academic researchers presented cutting-edge work and highlighted benefits for clinical trials, which test the safety and efficacy of a new drug. Katabi described a WiFi-like device that uses radio signals to monitor breathing and heart rate. It can also measure gait, detect falls, and monitor sleep and apnea. Katabi emphasized that “the device extracts this information by analyzing the radio waves in the environment. So, there is no overhead to the patient, and no need to wear sensors.” The device is currently deployed with Parkinson’s and Alzheimer’s patients and is used to understand the impact of the disease on mobility, sleep, and dependence on the caregiver.

“Can we leverage complex biological knowledge and vast amount of clinical and genomic data to change the cancer drug discovery process?” asked Dimitris Bertsimas, the Boeing Professor of Operations Research at the MIT Sloan School of Management. He is working on a data-driven approach that involves personalized genomic cancer therapy.

Caroline Uhler, the Henry L. and Grace Doherty Assistant Professor in EECS, described the spatial organization of the genome and early cancer detection using neural networks.

“Biomedicine is at an inflection point,” said Andrew Lo, the Charles E. and Susan T. Harris Professor at the MIT Sloan School of Management. As people heed the convergence of the science, engineering, and therapeutics — let’s also consider the economics, he said.

He described using computer algorithms for statistical analysis of the financial returns to biotech and pharmaceutical investments if they invest in a drug’s development. Machine learning models can finely estimate probabilities of success of clinical trials, he said.

“Investors want to know the chance of success,” he said. “You hear talk of Big Pharma getting out of Alzheimer’s because the failure rate in clinical trials have led them to see it as a “black hole.” But if you have more refined analytics that might provide some hope to investors and might attract them to invest.”

AI for better results

Other presentations delved into a wide range of improvements enabled by digital technologies. Barzilay described using machine learning to detect cancer with a complex neural model that can explain the why behind its decisions. “Our model offers interpretability with concise evidence. It takes neural networks and breaks data apart in smart ways to give you an explanation,” she said.

Tommi Jaakkola, the Thomas Siebel Professor in EECS, highlighted the use of machine learning in chemistry. He said it’s time to draw computationally on the millions of known reactions in databases only partially explored — such as articles in chemical, medical, or biological journals and in private repositories. “By digesting the information at scale we can really improve the state of the art,” he said. “The design, the discovery, the optimization. This area is on the verge of exploding.”

This work is currently developed as part of the Machine Learning for Pharmaceutical Discovery and Synthesis Consortium that includes leading pharmaceutical companies and MIT team of computer scientists and chemical engineers.  

David Sontag, an assistant professor in EECS, said he wants to see data from claims, clinical trials, disease registries and more used by machine learning for population-level understanding of disease progression.

The adoption of electronic health records in U.S. hospitals has increased nine-fold since 2008 from 9.4 percent to 83.8, he said with approval. But the challenges of machine learning using clinical data are significant, including the amount of missing and heterogeneous data.  

Ray Dorsey, the David M. Levy Professor of Neurology at the University of Rochester Medical Center, presented on the “tremendous insights” that Katabi’s technology is delivering for people with Parkinson’s disease.

“We can visualize both their location and frequency and movements and all that can be tracked accurately across long time spans. Until now, our perspective of a patient’s illness experience was episodic and limited,” he said. “Maybe next year, I can come back and say we have highly effective treatments for this disease.”

Shaping the future

During an afternoon panel, MIT President Emerita Susan Hockfield, a professor of neuroscience in the MIT Department of Brain and Cognitive Sciences, asked: “If we’re lucky, looking forward, how will the FDA onboard digital and machine learning devices?”

“Things have to change, but the fundamental that shouldn’t change is that you have to validate that your technology has human benefit and the benefits outweigh the risk for the intended uses,” said Robert Califf, the vice chancellor for health data science at Duke University and former FDA commissioner.

After the summit, Sharp, a pioneering molecular biologist who earned a Nobel Prize for his co-discovery of RNA splicing, said it had highlighted the promise of AI and digital technologies for improving the lives of patients.

“I expect that working groups will emerge from the meeting that will both formulate collaborative research programs and attract strong financial support,” Sharp said. “It was widely appreciated that the recent remarkable advances in AI and digital technologies will transform biomedical sciences and health care. This vision gave rise to palpable excitement in the audience that will move promise to accomplishment."

For additional information, visit the MIT News website.

 

Date Posted: 

Wednesday, April 11, 2018 - 9:30am

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Led by EECS Professors Barzilay and Katabi, MIT hosts a conference on new opportunities for collaboration.

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Using friends to fight online harassment

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CSAIL PhD student Amy Zhang led the development of the new Squadbox tool. Photo: Jason Dorfman/MIT CSAIL

Adam Conner-Simons and Rachel Gordon | CSAIL

Harassment has become ubiquitous on social media and in the online world; Twitter has been under fire for how it handles harassment, YouTube’s trending algorithm has occasionally promoted offensive videos, and reporting abuse on Instagram is still quite difficult.  

While current tools for harassment such as blocking users or filtering trigger words partially helps, a lot of online mistreatment is so subtle that an algorithm alone might not pick up on various cues.

But what if people could actually leverage their friends to help moderate their accounts and shield them from abusive messages?

A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) use that approach with “Squadbox,” a new crowdsourcing tool that enables people who have been the targets of harassment to coordinate “squads” of friends to filter messages and support them during attacks.
    
The team interviewed a range of scientists, activists, and Youtube personalities, and found that many people who are harassed on email rely on friends and family to shield themselves from abusive messages.

Senior author and MIT Professor David Karger says that Squadbox aims to make this so-called “friend-sourcing” more efficient and less work for its moderators.
        
“If you just give moderators the keys to your inbox, how does the moderator know when there’s an email to moderate, and which email has already been handled by other moderators?” says Karger. “Squadbox allows users to customize how incoming email is handled, divvying up the work to make sure there's no duplication of effort.”

Karger wrote the new paper with PhD student Amy Zhang and former MIT student and current software engineer Kaitlin Mahar '16. MNG '17. The team will present the work in April at ACM’s CHI Conference on Human Factors in Computing Systems in Montreal, Canada.

With Squadbox, the "owner" of the squad can set up filters to automatically forward incoming content to its moderation pipeline. Once an email arrives, a moderator decides which emails are harassment, and which can be forwarded back to the person’s inbox.

For example, let’s say a journalist wants to have a public email address to receive news tips, but fears having one because of how often she gets harassed by people who disagree with her reporting. She could create a Squadbox account with two close colleagues as moderators, and then use her account anywhere she wants to share her email address. Any email she receives at that address goes through her squad first.

“Previous solutions depended entirely on automated techniques, or were overly dependent on social solutions like simply giving one’s account information to a friend,” says Clifford Lampe, a professor of information at the University of Michigan. “This line of work helps provide a map for one hybrid solution to harassment that augments human support with tools in a meaningful way.”

While the team plans to extend the capabilities of Squadbox to work with social media platforms, they say that email is a particularly useful system for studying harassment.

“What’s interesting about email is that it’s not out in the open like Twitter or Facebook,” says Karger. “That means harassers may feel less accountability because their comments aren't public.”

Squadbox also lets users create “whitelists” and “blacklists” of senders whose emails will be automatically approved or rejected without moderation. Users can also deactivate and reactivate the system, read scores on messages’ toxicity, and even respond to harassers.

“Harassment is an inherently disempowering experience, and giving survivors options allows them to move back into control,” says Emily May, co-founder and executive director of the global anti-harassment initiative Hollaback! “Squadbox is designed to not just remind people that they have community around them, but to activate that community on their behalf.”

The team evaluated Squadbox on five pairs of friends, and found that using friends helped with fears of privacy and allowed for more tailored decisions for victims. However, users still worried that a friend might be sensitive to slow response times, and that the system could also be “spreading” the burden. The team says that having multiple moderators could potentially help this issue.
 
“Squadbox offers a tangible system of support for people who are harassed online by using other people,” says May. “We need to put survivors back in control and create communities strong enough to declare: this isn't the internet we want. It's not the world we want. And we're not going to stand for it anymore.”

For related content, visit the MIT News website.

Date Posted: 

Monday, April 9, 2018 - 10:00am

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Vinod Vaikuntanathan wins Edgerton Faculty Award

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Professor Vinod Vaikuntanathan. Photo: Courtesy of CSAIL

Vinod Vaikuntanathan, an associate professor in EECS, has been recognized for excellence with the 2017-2018 Harold E. Edgerton Faculty Achievement Award.

The honor lauds Vaikuntanathan, who also a principal investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL), for "his innovative and broadly-applicable work in cybersecurity, and for his wonderfully conversational and comprehensible lectures and inspiring discussions,” the award selection committee stated in its decision. The award was announced at a recent MIT faculty meeting.

The annual award was established in 1982 as a tribute to Institute Professor Emeritus Harold E. Edgerton, for his active support of junior faculty members. Each year, a committee presents the award to one or more non-tenured faculty members to recognize exceptional contributions in research, teaching, and service. 

Vaikuntanathan’s colleagues and students have commended him for his clear, approachable, and engaging style as a teacher and mentor, as well as for his contributions to the EECS cryptography community and curriculum. The School of Engineering also recognized his contributions in these areas with the Ruth and Joel Spira Award for Distinguished Teaching in 2016.

“Vinod is widely considered the best cryptographer of his generation,” one senior faculty colleague wrote in a nomination. “His teaching record is stunning; it is very rare for a junior faculty member to be considered one of the best lecturers in our department. His citizenship is exemplary and he has taken on a leadership role in the EECS and CSAIL communities.”

Vaikuntanathan studies encryption systems that protect the privacy of data, digital signatures that protect its integrity, and cryptographic protocols that allow organizations that don’t trust each other to collaborate and perform meaningful tasks while maintaining individual privacy. One example is fully homomorphic encryption (FHE), which enables encrypted computation without having to trust a cloud provider with sensitive data. The data are encrypted using a key that is known only to the user, but uses an FHE algorithm to perform computations on the encrypted data. Even if attackers managed to subvert the cloud, they get nothing of value as long as users keep their keys secret.

The selection committee noted that the state of the art in FHE is now based on methods that Vaikuntanathan invented, which are many orders of magnitude more efficient than previous techniques. His work has made major steps towards widespread adoption of FHE, while at the same time producing beautiful theoretical results.

Vaikuntanathan is globally sought out for lectures, tutorials, and participation in international conferences and workshops on cryptography and complexity theory. As of last year, he had given 60 invited presentations in 17 countries across four continents. He has also co-authored more 80 publications in proceedings of refereed conferences and journals. He holds five patents.

His additional career honors include an Alfred P. Sloan Research Fellowship and a National Science Foundation CAREER Award, among others.

Vaikuntanathan received a bachelor of technology degree from the Indian Institute of Technology Madras, and MS and PhD degrees in computer science from MIT. He was the Josef Raviv Postdoctoral Fellow at IBM’s Thomas J. Watson Research Center and a researcher at Microsoft Research Redmond. He served as assistant professor at the University of Toronto for two years before returning to MIT as an assistant professor of EECS in 2013, attaining the rank of associate professor in July 2015. He is also a co-founder and the chief cryptographer at Duality Technologies.

Among other EECS activities, Vaikuntanathan co-directs Masterworks, the annual EECS celebration of thesis research leading to the MS and MEng degrees. This year’s event, which is free and open to the public, will be held on April 26 from 5-6:30 p.m. on the Charles M. Vest Student Street on the first floor of the Stata Center.

 

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Monday, April 23, 2018 - 1:15pm

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The EECS faculty member is honored for his innovative work in cybersecurity and his engaging teaching style.

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Removing health-care barriers and boundaries

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Amar Gupta 

Eric Smalley | EECS Contributor

MIT’s Amar Gupta and his wife Poonam were on a trip to Los Angeles in 2016 when she fell and broke both wrists. She was whisked by ambulance to a reputable hospital. But staff informed the couple that they couldn’t treat her there, nor could they find another local hospital that would do so. In the end, the couple was forced to take the hospital’s stunning advice: return to Boston for treatment.

Because of the injury and delays in obtaining the needed surgery, Gupta declined an offer of an endowed professorship in Los Angeles, extending his stay at MIT beyond his one year as a visiting professor. In his view, the experience was bitter confirmation of the need for his work addressing dysfunction and inefficiency in the U.S. health-care system, and it inspired him to redouble those efforts.

Gupta, who teaches the EECS and IMES course Telemedicine and Telehealth for Enhancing Global Health (6.884/HST.S58), has been instrumental in several major technological advances at MIT and at two other universities where he held professorships. He pioneered content-based image search techniques on microcomputers and developed character-recognition technology widely used today for electronic check-processing. He developed neural-network algorithms for reading mammograms that dramatically reduce the incidence of false negatives and false positives. He also developed a neural network-based system to reduce a national pharmacy chain’s drug-inventory level from $1 billion to half that amount while maintaining the same overall probability for finding a drug in stock when needed.

But Gupta, who was the first senior research scientist at the MIT Sloan School of Management, has spent much of his career dealing with what comes after invention: deployment. He notes that there’s no shortage of innovative technologies that languish unused. Many fail to serve a need. Others are impractical. Still others have simply been blocked by institutional, legal, or policy hurdles. Gupta has worked to both persuade organizations to adopt useful innovations and to change laws hindering adoption. "Amar is among the small fraction of researchers who propose innovative ideas and who can also address the institutional and policy challenges related to broad use of their ideas," says Phillip Clay, former MIT Chancellor and professor emeritus in the MIT Department of Urban Studies and Planning.

The need for such expertise and experience is particularly acute in health care as the United States struggles to contain costs and reduce inefficiencies. The U.S. Department of Veterans Affairs (VA) alone spends $1 billion annually just to reimburse transportation costs incurred by veterans undergoing medical treatment, according to research published in Telemedicine and Journal and e-Health, the official journal of the American Telemedicine Association. In 2017, the VA announced plans to provide telemedicine services regardless of where patients and providers are located, disregarding state laws restricting interstate practice of telemedicine. Supporting such developments is Gupta’s challenge of the constitutionality of state laws and regulations that inhibit the practice of telemedicine, outlined in an article he co-authored, with Deth Sao, in Health-Matrix: The Journal of Law-Medicine, in 2012.

While doctors and state medical boards may prefer the tradition of state-level regulations, regulation of interstate commerce remains the domain of the U.S. federal government, Gupta notes. "I cannot think of another [computer science] faculty member who has written a similar controversial paper in a law journal and whose policy recommendations have led to such profound impact at the national level," says Ram Sriram, chief of the Software and Systems Division of the Information Technology Laboratory at the National Institute of Standards and Technology in Maryland.

Sriram is particularly interested in Gupta’s work in the area of health-care interoperability and his efforts to link information from electronic health record [EHR] systems, Internet of Things devices, pharmacy systems, and lab systems. Gupta is taking a consortium approach that was previously used to foster machine-based reading of amounts on bank checks, Sriram notes. Interoperability is crucial for the widespread adoption of telemedicine, and the adoption of banking technologies can serve as a model, Gupta explains. “We really need to have some rational way of thinking about telemedicine across state boundaries as well as across national boundaries,” he says. “If each of the states is going to have different laws, it becomes a much bigger barrier to employing it.”

A key component of Gupta’s work on telemedicine deployment is ensuring that students learn about the issues. In his popular telemedicine course, he emphasizes the practical over the theoretical by bringing in guest speakers from government, industry, and medical schools, a feature that’s especially popular with students. The new course received very high evaluation scores from students, a rare achievement, Clay notes.

The course “is a fantastic and quite unique forum for exploring telemedicine in all its dimensions, and Gupta’s experience and accomplishments make him the perfect person to run it,” says Jeffrey Flier, a Harvard University Distinguished Service Professor and former Dean of Harvard Medical School. Flier was a recent guest in the class.

The course resonates with many of the students personally. Sudhanshu Mishra ’17, from Bangalore, India, noted that his home country has a growing shortage of doctors given the rate of population growth and the capacity of Indian medical schools to produce doctors. “The only way the health-care needs of the population can be met is if there's an amplifying factor,” says Mishra, who is now enrolled in the EECS Master’s in Engineering program.  “So that's where telemedicine comes in.”

Mishra has seen it in action. His mother is a doctor, and she frequently receives text messages from remote patients with medical complaints, he says: “Often, she's able to figure out what's wrong and provide a course of action.”

In addition, Gupta’s concept of the 24-Hour Knowledge Factory involves using globally dispersed teams that can assure that work continues smoothly around the clock. The concept can also help address another long-standing problem: declines in the job performance of health-care professionals working overnight shifts, compared with their counterparts on daytime shifts.

With that in mind, Emory University recently transferred several doctors and nurses to Australia as part of the effort to provide better overnight service to patients in Atlanta. The medical team in Australia works 12 hours during daytime there, then hands things off to the Atlanta staffers, who work during their own daylight hours, then, in turn, hand things back to their Australian counterparts. Gupta is now analyzing data from the project. “Right now, they're only looking after American patients, and they've only been licensed to practice in the U.S.,” he says. “But I can see a day when all this happens on a global basis.”

In most countries today, patients no longer need to fly thousands of miles for treatment of injuries, suffering additional pain and discomfort due to delays in medical attention. Widespread adoption of telemedicine concepts will allow more patients to be treated at or near home. Gupta’s harrowing experience has simply strengthened his resolve to continue working toward a goal he sums up as “health-care for all: better, quicker, and less expensive.”

Date Posted: 

Monday, May 7, 2018 - 5:30pm

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Amar Gupta of EECS and IMES is working toward widespread adoption of transformative telemedicine.

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Computation counts: Python-based course sees enormous growth

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Professor Eric Grimson, Chancellor for Academic Advancement, illustrates the concept of random sampling with a video featuring Professor John Guttag as a blindfolded archer. Photo: Lillie Paquette, School of Engineering

Meg Murphy | School of Engineering

 

When James Quigley applied to MIT, he didn’t need an algorithm to tell him getting in wasn’t a high-probability outcome. An Army veteran attending community college in California, he possessed a talent for math, a desire to do big things, and a sobering group of friends who insisted: “Mortals don’t get into MIT.” Quigley knew a dare when he heard one. As for probability measures, those he chose to ignore.

Now a second-year student at the Institute, Quigley was recently sitting in a lecture for 6.00 (Introduction to Computer Science and Programming Using Python). The topic of the day was using a computer simulation to estimate the value of an unknown quantity: the probability of winning at solitaire. He’s taking the class to learn to think like a computer scientist, he says. He speaks of Python, his first real computer programming language, with awe.

“When I first started Python, I basically felt like I was learning some unfathomable witchcraft. Many of the concepts still feel hard to grasp, and that feeling is what made me love it,” says Quigley. “People can use 1s and 0s to cure diseases, unite people, or destroy nations. Who wouldn’t be fascinated by something like that?”

It has been around since 2005, but over the last few semesters, 6.00, like the Course 6 major itself, has seen enormous growth in enrollment, with 424 students from 10 departments enrolled in 6.0001 this spring. (6.00 was recently split into two half-term subjects, 6.0001 and 6.0002.) About 60 percent are first- or second-year students, according to the class roster, with the remainder a mix of juniors, seniors, and graduate students. In spring 2016, 239 students enrolled, followed by 425 that fall. By the fall of 2017, it rose to 507. “It’s 2018, and even children are learning to code,” Quigley says.

“We teach computational thinking. It involves far more than coding. We start out with programming, which involves the creative application of math and critical thinking,” says Ana Bell, a lecturer in the Department of Electrical Engineering and Computer Science. She delivers the majority of the lectures in 6.0001. “Programming requires you think about math in a deeply logical manner while following the rules of language and being creative in your constructs,” she says. “With programming at the base, you can use computations and simulations to model and attempt to explain almost everything around us. That’s computer science.”

“Even if you never again write a program in your life,” says Quigley, “coding forces you to account for every possibility. It also teaches you that being wrong doesn’t mean you don’t progress. When I code, I’m wrong over and over until finally I’m right,” he adds.

A computing mindset

In one of MIT’s largest lecture halls, Quigley listens intently as computer scientist Eric Grimson, chancellor for academic advancement, describes Monte Carlo simulation, a method of estimating the value of an unknown quantity using principles of inferential statistics. In rapid succession, Grimson describes using randomized computation to solve problems that are not inherently random; employs coin flips and roulette wheels to explore quantifying variation in data; and illustrates the concept of random sampling with a staged video featuring MIT Professor John Guttag, the originator of 6.00, as a blindfolded archer.

Bell, who is sitting in the front row, smiles as she watches the video with the class. On screen, she helps Guttag simulate a computer programming method via a campy scene that involves fleeing students and arrows piercing books and furniture. It is all part of the fun for Bell, who has loved programming since building a computer at age 11. She also co-teaches 6.0002 (Introduction to Computational Thinking and Data Science), an additional class offered on the heels of the introductory course. The majority of 6.0001 students, such as Quigley, remain for the advanced section.

Bell enjoys guiding novices through the sometimes intimidating realm of computer science. She remembers how difficult it was, at first, to switch her own way of thinking and grasp tough concepts, such as object-oriented programming. “Sometimes students come to my office and they just don’t get it — but I know they can get it.” So, she’ll take a multipronged approach: draw something on the chalkboard, write the code, run the code with test cases, explain it in words. “Sometimes it takes them a really long time — but the switch occurs. They switch to a computational way of thinking; the students become the computer.”

First-year student Darya Guettler says the material resonates with most students because analyzing data is a core element in all engineering and science disciplines. “I have also found that I am able to look at seemingly random processes in the world as quantifiable now, so this class has given me a new perspective through which to view the world,” she says.

The appeal of mastering such thinking is clear to Michael Gritzbach, a visiting undergraduate student at Harvard University. His current focus is Chinese foreign policy and intensive Russian, but he nevertheless enrolled in 6.0001/2 at MIT. “Computer science is becoming more important for all aspects of our lives — in apps, games, or social media algorithms that influence society and politics,” says Gritzbach, who studies management, philosophy, and economics in Frankfurt.

According to Guttag, who has helped shepherd 6.00/6.0001/6.0002 from the beginning, 6.0001/2 is often difficult for students from non-computer science disciplines, but in a good way. “For a lot of students, it’s a struggle because it’s a very different way of thinking,” he says. “But at the end of the day, they’re glad they learned the material. And they see that computer science isn’t all about learning to build operating systems or compilers, or about designing clever data structures. This field is really about learning to use computation to do things that matter.”

People with no prior exposure to computer science or programming can also learn to think computationally by signing up for the two-course sequence for free on MITx. “We put a bunch of the course material on MITx so students have the ability to watch the videos and learn at their own pace,” says Bell. “It’s awesome to see the class being taught to the world.”

Quigley, like his classmates, recognizes the potential. “I want to do more than just coding; I want to build things,” he says, describing why he chose to major in electrical engineering and computer science. “I’ve heard it said that computer engineering is taking lightning, putting it in a box, and tricking it to think. Sounds like fun to me.”

 

Date Posted: 

Wednesday, May 9, 2018 - 5:30pm

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Students are flocking to 6.00 (Introduction to Computer Science and Programming Using Python), where they learn not just coding but computational thinking.

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The tenured engineers of 2018

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Newly tenured faculty are: (clockwise from top left) Dirk Englund, Yury Polyanskiy, and Adam Chlipala (all EECS), Kenneth Kamrin (MechE), Qiqi Wang (AeroAstro), and David Sontag, and Vinod Vaikuntanathan (both EECS).

School of Engineering / EECS Staff

 

Five EECS faculty members are among seven from the School of Engineering who have received tenure from MIT. The five – Adam Chlipala, Dirk Englund, Yury Polyanskiy, David Sontag, and Vinod Vaikuntanathan – are joined by Ken Kamrin in the Department of Mechanical Engineering and Qiqi Wang in the Department of Aeronautics and Astronautics.

"I am proud to announce this year’s cohort of newly tenured faculty in the School of Engineering,” said Anantha Chandrakasan, dean of the School of Engineering. “Their work as scholars and educators is inspiring to our entire community. We will benefit immensely from their work.” 

Following are profiles of the newly tenured EECS faculty members:

Adam Chlipala is a leader in the emerging area of integrated software design and verification. His contributions include building general computational infrastructure (based on the Coq proof-management system) to support programming, formal verification, and automatic code generation, as well as applications to verification of many types of software and hardware systems. 

Specific contributions include the Bedrock system for specifying and verifying software designs, the Fiat framework for automatic code generation, the FSCQ project for verifying file systems, the Kami system for verifying hardware designs, and the Fiat elliptic curve cryptography library. Google recently adopted Chlipala’s Fiat cryptographic library for its Chrome browser, and his formal specification for the RISC-V processor was adopted as the official specification for the RISC-V instruction set architecture. He is a principal investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL).

Chlipala helped develop the new undergraduate Fundamentals of Programming course (6.009), developed a new graduate course on Foundations of Program Analysis (6.820), and actively participates in EECS graduate admissions. He has received a National Science Foundation (NSF) CAREER Award, a Symposium on Operating System Principles (SOSP) best-paper award, and two Communications of the Association for Computing Machinery (CACM) research highlights

In his research, Dirk Englund focuses on developing of solid-state photonic and quantum devices and systems and their use in quantum computation, communications, and sensing. His work emphasizes leveraging deep insight in quantum information theory and optics to develop engineered systems that dramatically advance the field. His stated vision is ambitious: to create the quantum internet, where entanglement is distributed worldwide. Significant contributions range from achieving record performance with a practical high-dimensional quantum key distribution scheme to performing quantum transport simulations using photonic integrated circuits. He leads the Quantum Photonics Laboratory in the Research Laboratory of Electronics (RLE).

Englund has taught a variety of EECS classes, including Introduction to EECS (6.01), Oral Communication (6.UAT), and Seminar in Undergraduate Advanced Research (6.UAR, the SuperUROP course). He also helped create the EECS Communications Lab, which provides resources for graduate students for oral and written communications, and, with Vinod Vaikuntanathan, has co-directed Masterworks, the department’s annual celebration of research leading to the SM and MEng degrees. His awards include a Sloan Research Fellowship in Physics, the Presidential Early Career Award for Scientists and Engineers, and the Optical Society of America Adolph Lomb Medal, the top award for a young researcher in optics.

Yury Polyanskiy is a well-known theorist who works on information processing systems that arise in communication, control, and learning. He is widely known for his pioneering work on finite blocklength information theory. His work developed fundamental results in non-asymptotic information theory, providing tight lower and upper bounds for the capacity of a given blocklength. He also has important contributions in a broad set of areas including properties of information measures, discrete geometry and combinatorics, and statistical learning theory. The tools and relations he developed for information measures enabled him to settle long-standing conjectures in network information theory and address fundamental questions in control and high-dimensional statistics. 

Polyanskiy is a member of the Laboratory for Information and Decision Sciences (LIDS), the Institute for Data, Systems, and Society (IDSS), and the Statistics and Data Science Center (SDSC). He has taught the undergraduate courses Introduction to EECS (6.02) and the SuperUROP course (6.UAR). He is currently co-developing a new foundation-level class, Introduction to Data Science (6.S077). He also teaches the graduate classes Information Theory (6.441) and Fundamentals of Probability (6.436), and he co-developed a new graduate class, Tools of Discrete Probability (6.265).

Awards include an NSF CAREER Award, the IEEE Information Theory best-paper award, IEEE International Symposium on Information Theory (ISIT) best student-paper awards (twice), and the EECS Jerome H. Saltzer teaching award.

David Sontag focuses on research in machine learning and applying machine learning to health care. In machine learning, he focuses on graphical models, which provide a mathematically rigorous and computationally efficient way to represent dependencies between a hidden (latent) structure and observations. His contributions include new highly efficient algorithms for learning, inference, and prediction with graphical models from real world data, and theoretical results in a form of error bounds and correctness proofs that establish a new framework for theoretical analysis of approximate and exact learning and inference in graphical models.  

Sontag is a pioneer in applying machine learning expertise to health care, where he has significantly advanced the state of the art in building predictive models from electronic medical records. His expertise in clinical decision making has led him to build novel formulations of machine-learning problems. The analytical tools and algorithms he develops to solve those problems are advancing machine-learning fundamentals and having an impact beyond health care.

Sontag is also the Hermann L. F. von Helmholtz Career Development Assistant Professor in the Institute for Medical Engineering and Science (IMES) and principal investigator in CSAIL. His honors include an NSF CAREER Award, faculty awards from Google, Facebook, and Adobe, several best-paper awards, and the EECS George M. Sprowls Award for Best PhD Thesis.

Vinod Vaikuntanathan, a leader in theoretical security, focuses on techniques for storing, accessing, and computing with encrypted data. His best-known work is on Fully Homomorphic Encryption, Functional Encryption, and Program Obfuscation, among others. His work involves establishing clear mathematical definitions of security properties, identifying key hardness assumptions on which to base security claims, devising new algorithms, and proving their security properties. Most of his work uses Lattice-Based Cryptography, which is based on hardness assumptions for problems involving integer lattices; such assumptions might be justified even in a future with powerful quantum computers. He is a principal investigator in CSAIL.

Vaikuntanathan regularly teaches Introduction to Algorithms (6.006) and Analysis of Algorithms (6.046), and also teaches graduate cryptography courses. He has served on the EECS graduate admissions committee and, with Dirk Englund, co-directed the department’s annual EECS Masterworks poster session.

His awards include an NSF CAREER Award, a Sloan Research Fellowship, a Microsoft Research faculty fellowship, and an EECS Ruth and Joel Spira Award for teaching. Most recently, in April 2018, he received MIT’s annual Harold E. Edgerton Award for Faculty Achievement, presented to junior faculty for outstanding research, teaching, and service.

For additional details, visit the MIT News website.

 

Date Posted: 

Thursday, May 10, 2018 - 2:45pm

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MIT has granted tenure to seven School of Engineering faculty members, including EECS Professors Chlipala, Englund, Polyanskiy, Sontag, and Vaikuntanathan.

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Revealing the results of students' real-world research

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2018 SuperUROP Showcase + Masterworks event. Photo: Gretchen Ertl

By Kathryn O’Neill | EECS Contributor

Watch video here!

Dozens of MIT undergraduate and graduate students unveiled the results of extensive research projects during the high-energy SuperUROP Showcase + Masterworks posster sessions at MIT’s Stata Center in late April.

Addressing topics as diverse as gene expression, smart-home sensing, aircraft propulsion, and theater promotion, about 130 participants in the Advanced Undergraduate Research Opportunities Program – better known as SuperUROP– presented the results of their year-long projects in two shifts. Immediately following the SuperUROP sessions, nearly 50 master’s-degree recipients and candidates from the Department of Electrical Engineering and Computer Science (EECS) shared their own research results.

“It’s so satisfying to see the fruition of all this hard work,” said Anantha Chandrakasan, dean of the School of Engineering. “The diversity of projects is impressive, as is the level of rigor.”

SuperUROP Showcase

Senior Nitah Onsongo, a computer science and engineering (6-3) major, for example, took advantage of the fact that, thanks to an anonymous donor, SuperUROP now supports research involving the School of Humanities, Arts, and Social Sciences (SHASS). Onsongo used machine learning, digital media, and web-development languages to create a tool designed to interest more people in theater. The experience left her an enthusiastic proponent of SuperUROP: “I really encourage everybody to enroll in this program sometime during their years here, because it’s helped me to practically apply my skills before going to industry.”

Junior Stephanie Ren, also in 6-3, took a more traditional technical SuperUROP route. She developed a system that helps a smart-home sensing device keep track of people inside their houses, and she especially enjoyed the time she spent in the lab. “You’re working toward a problem no one has solved yet,” Ren said. “Doing that exploration is very different from taking classes.”

Chandrakasan launched SuperUROP in EECS in 2012, when he was department head. The program expanded to the full School of Engineering in 2015 and to SHASS in 2017. SuperUROP provides students with an intensive graduate-level research experience supported by a two-term seminar (6.UAR) that covers everything from designing experiments to presenting results.  “It’s really a compressed version of life in research,” Dirk Englund, an associate professor in EECS and an instructor for 6.UAR.

This year’s SuperUROP class includes students from Aeronautics and Astronautics (AeroAstro), Biological Engineering, Civil and Environmental Engineering (CEE), and Chemical Engineering (ChemE), as well as EECS. Many received titles reflecting theindustrial sponsors, foundations, and alumni donors whose contributions supported their research.

The 2018 SuperUROP Showcase — which featured 66 big-screen electronic poster boards arrayed all along the Vest Student Street on the Stata Center’s first floor — attracted a steady stream of students, faculty, staff, alumni, and industry representatives. Audience members clustered around posters, giving participants a chance to present their work and answer questions in real time.

“It’s a great opportunity to develop professional presentation skills,” said senior Eric Wadkins (6-3), who described for visitors how he used techniques such as Bayesian inference to help a microscope learn where it is on a sample.

“I think the length of the SuperUROP is such that you can really get something done,” said Englund, who supervised Wadkins during the year-long project and noted that the work has already led to a patent application. In Wadkins’ case, Englund said: “He’s given normal microscope a brain to make decisions on its own.”

Some who attended the event came because it offers an opportunity to get a sneak peek at the research taking place across the Institute. “It’s good to see technology in its earliest and rawest form,” said Jake Harrison, a technology scout for Samsung.

Deborah Campbell, associate technology officer for Lincoln Laboratory, praised the “exceptional quality and diversity” of the 2017-2018 SuperUROP projects. “It was clear that the students learned a lot and made significant contributions to the areas they worked in,” noted Campbell, whose organization sponsored 12 SuperUROP scholars this year. “They communicated this with clear and concise presentations, high-quality posters and demonstrations, and insightful answers to questions.”

Ten SuperUROP Scholars received audience-choice awards for their presentations, including Rene Garcia Franceschini of CEE, Erica Ding of ChemE, and Archis Bhandarkar, Nicholas Charchut, Sharlene Chiu, Emily Damato, Kathy Muhlrad, Ryan Prinster, Jason Villanueva, and Larry Wang, all of EECS. Faculty-choice best-poster awards will be announced later on the EECS website.

Masterworks

During the Masterworks session, EECS master’s students presented the results of thesis research leading to the master of engineering (MEng) and the master of science (SM) degree. Their projects addressed questions in fields ranging from health care to robotics to sustainable energy. As the SuperUROP scholars had, Masterworks participants engaged in lively discussions with attendees about their research approaches and results.

After the session, Englund, who co-directed Masterworks with fellow EECS Associate Professor Vinod Vaikuntanathan, presented three “audience-choice” awards for the best Masterworks posters. Rumen Hristov received first place for “Adding Identity to Device-Free Localization Systems in the Wild.” Second place went to Mazdak Abulnaga for “Visualizing the Placenta in a Familiar Way.” Third prize was awarded to Tathagata Srimani for “Energy Efficient Computing from Nanotubes to Negative Capacitance.” In addition, Rumya Raghavan ’17 won the Masterworks Scavenger Hunt for correctly answering the most questions about research discussed on the posters. All four students received prizes provided by Masterworks sponsor Samsung.

Faculty choices for the best Masterworks posters will be announced later on the EECS website.

Date Posted: 

Friday, May 11, 2018 - 1:00pm

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SuperUROP and Masterworks participants shared the findings of their research projects during high-energy poster sessions.

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SuperUROP Scholars

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Photo: Gretchen Ertl

EECS Staff

 

The 2017-2018 SuperUROP Scholars celebrated the completion of their year-long research efforts in mid-May 2018 with a class photo and a closing reception. About 130 undergraduates from EECS and other participating departments received certificates commemorating their achievements.

During a brief ceremony, Anantha Chandrakasan, dean of the School of Engineering, praised the exceptionally high quality of the students' projects and presentations. Chandrakasan, who founded SuperUROP while EECS department head, noted that many past SuperUROP Scholars have gone on to publish the results of their research or give presentations at professional conferences.

Several SuperUROP scholars received best-project awards shortly after the closing reception:

 

  • Andrew Ilyas received a 2017-2018 SuperUROP Award for his project "Training GANS with Optimism," supervised by Professor Constantinos Daskalaskis.
  • Ekin Karasan received the Robert M. Fano Award for her project "An Enhanced Mechanistic Model for Capnography, with Application to CHF-COPD Discrimination," supervised by Professor George Verghese.
  • Andrew Rouditchenko received a 2017-2018 SuperUROP Award for his project "The Sound of Pixels," supervised by Professor Josh McDermott.
  • Diana Wofk received a 2017-2018 SuperUROP Award for her project "Energy-Efficient Deep Neural Network for Depth Prediction," supervised by Professor Vivienne Sze.

For more about the program, visit the SuperUROP website or visit the MIT News website to read articles, see photos, and view a brief video of the Spring 2018 SuperUROP Showcase poster session.

Date Posted: 

Friday, May 18, 2018 - 3:00pm

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The 2017-2018 SuperUROP Scholars celebrated the completion of their year-long research projects with a class photo and a reception. Congratulations to all!

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EECS Celebrates 2018: Recognizing the department's outstanding contributors

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EECS Staff

Students, faculty, staff, and special guests came together for EECS Celebrates, the department's annual awards ceremony and reception. The department presented nearly 60 awards during the May 18 event.

A highlight of this year's celebration was the new Seth J. Teller Award for Excellence, Inclusion, and Diversity. Named for the late EECS professor, the award honors members of the MIT community who embody those three values through work, research, or educational innovation.

The inaugural winners are: Irene Chen, a PhD candidate in EECS, and Marzyeh Ghassemi, a postdoctoral associate in the Computer Science and Artificial Intelligence Laboratory (CSAIL). Both were honored for serving as mentors and undertaking other activities to improve diversity and inclusion. Teller's widow, Rachel Zimmerman, and daughters, Sophia and Julia, attended the ceremony to present the awards.

Click below to see a photo slideshow, which is followed by a full list of this year's awards. All photos by Gretchen Ertl.

Created with flickr slideshow.

 

 

FACULTY AWARDS

Frank Quick Faculty Research and Innovation Fellowship (FRIF)
Devavrat Shah, Professor of EECS

EECS Faculty Research and Innovation Fellowship (FRIF)
Nickolai Zeldovich, Professor of EECS

Louis D. Smullin (’39) Award for Excellence in Teaching
Joseph Steinmeyer, Extraordinary Lecturer

Jerome H. Saltzer Award for Excellence in Teaching
Robert C. Berwick, Professor, Computational Linguistics and Computer Science & Engineering

Burgess (1952) & Elizabeth Jamieson Prizes for Excellence in Teaching
Erik Demaine, Professor of EECS
Dennis M. Freeman, Henry Ellis Warren (1894) Professor of Electrical Engineering

Ruth and Joel Spira Awards for Excellence in Teaching
Regina Barzilay, Delta Electronics Professor of EECS
John Tsitsiklis, Clarence J. LeBel Professor of EECS

EECS Outstanding Educator Awards
Stefanie Mueller, X-Consortium Career Development Assistant Professor of EECS
Tao B. Schardl, Postdoctoral Associate, CSAIL

Capers and Marion McDonald Award for Excellence in Mentoring and Advising
Ronitt Rubinfeld, Professor of Computer Science and Engineering 

IEEE/ACM Best Advisor Award
Gim P. Hom, Lecturer, EECS

HKN Best Instructor Award
Hari Balakrishnan, Fujitsu Professor of EECS

Department Head Special Recognition Award
Igor Gilitschenski, Senior Postdoctoral Associate, CSAIL
Lukas B. Murmann, PhD Candidate
Feras Saad, PhD Candidate

Richard J. Caloggero Award
Rob Miller, EECS Education Co-Officer and Distinguished Professor in Computer Science

 

STUDENT AWARDS 

Paul L. Penfield Student Service Award
Alex Jordan Hanson

Carlton E. Tucker Teaching Award
Megan Marie Fuller

Harold Hazen Teaching Award
Fabian A. Kozynski Waserman

Frederick C. Hennie III Teaching Awards
Timothy Kaler
Anne K. Kelley
Remi Mir
Tally Portnoi
Shraman Ray Chaudhuri
Mayuri Sridhar
Xuhong (Lisa) Zhan

Undergraduate Teaching Assistant (UTA) Award
Olivia Brode-Roger

Jeremy Gerstle UROP Award
Uma Roy
Project: Distributed Uncertainty Estimation for Variational Inference
Supervisor: Tamara Broderick, ITT Career Development Assistant Professor of EECS

Morais (1986) and Rosenblum (1986) UROP Award
Rujie Yao
Project: Continuous Removal of Nonviable Suspended Mammalian Cells and Debris from Bioreactors Using Inertial Microfluidics
Supervisor: Jongyoon Han, Professor of EECS and Biological Engineering

Anna Pogosyants UROP Award
Douglas Stryker
Project: Splines in Shape Difference Space
Supervisor: Justin Solomon, X-Consortium Career Development Assistant Professor of EECS

Licklider UROP Award
Xin Wen
Project: ColorMod: Recoloring 3D Printed Objects Using Photochromic Inks
Supervisor: Stefanie Mueller, X-Consortium Career Development Assistant Professor of EECS

Robert M. Fano UROP Award
Ekin Karasan
Project: An Enhanced Mechanistic Model for Capnography, with Application to CHF-COPD Discrimination
Supervisor: George Verghese, Professor of EECS

2017-2018 SuperUROP Awards
Andrew Ilyas
Project: Training GANS with Optimism
Advisor: Constantinos Daskalaskis, Associate Professor of EECS

Andrew Rouditchenko 
Project: The Sound of Pixels
Advisor: Josh McDermott, Middleton Career Development Assistant Professor, Department of Brain and Cognitive Science

Diana Wofk
Project: Energy-Efficient Deep Neural Network for Depth Prediction
Advisor: Vivienne Sze, Associate Professor of EECS

George C. Newton Undergraduate Laboratory Prize (6.111)
Katherine Shade & Melinda Szabo  
Project: Virtual Softball

Northern Telecom/BNR Project Award: Best 6.111 Project
Nicholas Waltman & Mike M. Wang
Project: Live-Action Pong

David A. Chanen Writing Awards (for Writing in 6.033)
David J. Amirault
6.033: System Critique: MapReduce

Temi T. Taylor
System Critique: Map Reduce

Morris Joseph Levin Award for Masterworks Thesis Presentation
Mazdak Abulnaga
Title: Visualizing the Placenta in a Familiar Way
Supervisors: Polina Golland, Professor of EECS; Justin Solomon, X-Consortium Career Development Assistant Professor of EECS

Tathagata Srimani
Title: Energy-Efficent Computing: From Nanotubes to Negative Capacitance
Supervisor: Max Shulaker, Emmanuel E. Landsman (1958) Career Development Assistant Professor of EECS

David Adler Electrical Engineering MEng Thesis Awards
First Place: Catherine Medlock
Title: Optimality of Empirically Generated Receiver Operating Characteristic Curves
Supervisor: Alan V. Oppenheim, Ford Professor of Engineering  

Second Place: Saumil Bandyopadhyay
Title: Frequency Down-Conversion for Quantum Networking with Nitrogen-Vacancy Center in Diamond
Supervisor: Dirk Englund, Associate Professor of EECS

Charles  & Jennifer Johnson MEng Computer Science Thesis Awards
First Place (1 of 2): Andres Erbsen
Title: Crafting Certified Elliptic Curve Cryptography Implementations in Coq
Advisor: Adam Chlipala, Associate Professor of Computer Science

First Place (2 of 2): Jade Philipoom
Title: Correct-by-Construction Finite Field Arithmetic in Coq
Advisor: Adam Chlipala, Associate Professor of Computer Science

Second Place: Bowen Baker
Title: Towards Practical Neural Network Meta-Modeling
Advisors: Cesar Hidalgo, Associate Professor of Media Arts and Sciences; Nikhil Naik, Postdoctoral Fellow, MIT and Harvard

Francis Reintjes Excellence in 6-A Industrial Partnership Award
Alex Sloboda
Project: AC-Coupled Ripple Reduction Method for Chopper-Stabilized Amplifiers
Supervisor: Charles Sodini, LeBel Professor of Electrical Engineering
Company: Analog Devices

STARTMIT AWARDS

StartMIT Hard Tech Problem & Solution Citation: ECTOTHERM 
Anton Cottrill
Volodymyr Koman
Wei Sun Leong

StartMIT Hard Tech Problem  Solution Citation: METASTORAGE
Gian Carlo Correa
Antoni Forner Cuenco
Laureen Meroueh
Ruitao Wan

StartMIT Most Promising Business Idea: NEXTILES
George Sun
Jodie Zuo

StartMIT Most Promising Business Idea: TANK IT EASY
Aymar Christian de Lichterveldte
Lina Gonzalez
Francesco Maurelli
Sayuri Ozaki

StartMIT Best Undergraduate Pitch: SILOS
Mesert Kebed
Marla E. Odell

StartMIT Student Audience Choice: FOCUS
Jesus A. Mathus
Alex Nordin

ADDITIONAL AWARDS

The following additional awards to EECS faculty were also acknowledged during the EECS Celebrates ceremony:

Bose Award for Excellence in Teaching (presented by the School of Engineering)
Srini Devadas, Webster Professor of EECS

Innovative Seminar Award (presented by the Office of the Vice Chancellor as part of the Freshman Advisors Awards)
Dennis M. Freeman, Henry Ellis Warren (1894) Professor of Electrical Engineering

MIT Harold E. Edgerton Faculty Achievement Award (presented to junior faculty members for exceptional teaching, research, and service)
Vinod Vaikuntanathan, Associate Professor of EECS

MIT Gordon Y Billard Award (presented in recognition of “special service of outstanding merit”)
Christopher Terman, Senior Lecturer, EECS

NOTE: Award winners seeking access to slideshow photos may request access to the private awards website by contacting eecs-communications@mit.edu.

Date Posted: 

Friday, May 25, 2018 - 1:45pm

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The annual awards ceremony honored a variety of faculty members and students for their achievements.

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MIT faculty approves new joint urban science major to launch in fall 2018

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Photo: John Phelan

School of Architecture and Planning | School of Engineering

Urban settlements and technology around the world are co-evolving as flows of population, finance, and politics are reshaping the very identity of cities and nations. Rapid and profound changes are driven by pervasive sensing, the growth and availability of continuous data streams, advanced analytics, interactive communications and social networks, and distributed intelligence. At MIT, urban planners and computer scientists are embracing these exciting new developments.

The rise of autonomous vehicles, sensor-enabled self-management of natural resources, cybersecurity for critical infrastructure, biometric identity, the sharing or gig economy, and continuous public engagement opportunities through social networks and data and visualization are a few of the elements that are converging to shape our places of living.

In recognition of this convergence and the rise of a new discipline bringing together the Institute’s existing programs in urban planning and computer science, the MIT faculty approved a new undergraduate degree, the bachelor of science in urban science and planning with computer science (Course 11-6), at its May 16 meeting.

The new major will jointly reside in and be administered by EECS and the Department of Urban Studies and Planning (DUSP).

Combining urban planning and public policy, design and visualization, data analysis, machine learning, and artificial intelligence, pervasive sensor technology, robotics, and other aspects of both computer science and city planning, the program will reflect how urban scientists are making sense of cities and urban data in ways never before imagined — and using what they learn to reshape the world in real-time.

“The new joint major will provide important and unique opportunities for MIT students to engage deeply in developing the knowledge, skills, and attitudes to be more effective scientists, planners, and policy makers,” says Eran Ben-Joseph, DUSP department head. “It will incorporate STEM education and research with a humanistic attitude, societal impact, social innovation, and policy change — a novel model for decision making to enable systemic positive change and create a better world. This is really unexplored, fertile new ground for research, education, and practice.”

The goal of the program is to train undergraduates in the theory and practice of computer science and urban planning and policy-making including ethics and justice, statistics, data science, geospatial analysis, visualization, robotics, and machine learning.

“The new program offers students an opportunity to investigate some of the most pressing problems and challenges facing urban areas today,” says Asu Ozdaglar, EECS department head. “Its interdisciplinary approach will help them combine technical tools with fundamental skills in urban policy to create innovative strategies and solutions addressing real-world problems with great societal impact.”

Although this field draws on existing disciplines, the combination will shape a unique area of knowledge. Practitioners are neither computer scientists nor urban planners in a conventional sense, but represent new kinds of actors with new sets of tools and methodologies. Already, in areas as diverse as transportation, public health, and cybersecurity, researchers and practitioners at MIT are pioneering work along these lines, demonstrating the potential for collaborative efforts.

“Every now and then, the world puts in front of us new problems that require new tools and forms of knowledge to address them,” says Hashim Sarkis, dean of the School of Architecture and Planning. “The growing challenges that cities are facing today has prompted us to develop this new major in urban science. We are combining the tools of AI and big data with those of urban planning, the social sciences, and policy. We are also mobilizing SA+P’s design capacities to unleash the creative potentials of quantitative intelligence through urban science and other collaborations with Engineering and the other schools at MIT.”

The urban science major proposes a comprehensive pedagogy, adding new material and integrated coursework. A centerpiece of this integration will be the degree’s “urban science synthesis lab” requirement, where high-tech tools will be brought together to solve real-world problems.

“This degree program will broaden our students’ perspectives and deepen their exposure in new and exciting directions,” says Anantha P. Chandrakasan, dean of the School of Engineering. “Just like the 6-14 program that EECS and Economics launched last year, this new course of study will empower and challenge students and researchers to think in new ways and form new connections. The value and relevance of computational thinking just keeps growing.”

The new major will be available to all undergraduates starting in fall 2018.

For more information on this story, including a media contact, visit the MIT News website.

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Tuesday, June 5, 2018 - 4:15pm

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An unexpected ambition evolves from one student's MIT experience

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EECS Senior Annamarie Bair                                                                        Photo: Lillie Paquette, School of Engineering

Meg Murphy | School of Engineering

 

Senior Annamarie Bair was determined to become a medical doctor when she arrived at MIT from the Midwest nearly four years ago. She was fascinated by neuroscience but had yet to channel that passion toward what became her true focus: artificial intelligence and health care.

“I remember joking to my friends in Michigan to watch out, I might return from MIT a computer science nerd. And guess what, it’s happening,” she says. Bair will graduate on June 8 with a degree in computer science and engineering and then go on to a summer internship at Microsoft.

Today she shrugs off past certainties with a laugh. “One thing I’ve learned at MIT is that you have to be willing to change course,” she says, describing an intellectual journey influenced by pivotal classes, influential professors, graduate student mentors, friendships, internships, and the overall atmosphere produced by a “community of passionate people.”

“Everyone at MIT has something they’re really passionate about, and it’s not even necessarily engineering,” she says. “It’s cool to see what makes people tick. You can touch on a lot of subjects and people can be interested, but when you hit on something they really care about, their eyes light up, and you’re like, ‘Wow, this is it. They’re going to do great things in this area.’ Without fail, everyone at MIT has this passion, even if they are still finding it in themselves.”

Following a passion

Several weeks into her second semester at MIT, Bair realized, via an introductory computer science course, an unexpected passion for ideas in the field. “It felt like a different way of thinking than I'd seen before — but also mirrored ways I thought,” she says. “I wanted to learn more about it. And I just kind of couldn't stop.”

She switched from a premed orientation to a major in computer science and incorporated neuroscience as a minor, a combination that led to an interest in artificial intelligence. “In my neuroscience courses, I’m always thinking: What’s the parallel in computer science?” says Bair. “And in my computer science classes, I’m asking: Does the brain do anything like this?”

Her classes inspired reading about AI and consciousness. She loved exploring theoretical problems in both computer science and neuroscience. As a senior, Bair dove into an Advanced Undergraduate Research Opportunities Program (SuperUROP) research project in the lab of Peter Szolovits, an MIT professor of computer science and engineering and head of the Clinical Decision-Making Group within the Computer Science and Artificial Intelligence Laboratory (CSAIL). The group focuses on applying machine learning methods to health care and medicine.  

“We’re looking at gene-expression data,” she says with excitement. “We’re using machine-learning methods to track impacts on gene expression. We’re ultimately providing a tool for biological researchers to more easily identify which genes to focus on and where they should target research in the future.”

Expanding horizons

When Bair envisions a future career, her thinking is more flexible than it once was. She plans to return to MIT in the fall to do graduate work in the lab of Szolovits. After that, she will see.

“I think it might be nice to go into industry research. I know of research projects at Microsoft, Facebook, and Google that look cool,” she says. “I’d like to get a PhD and go toward that. All I know is that I want to work on machine learning and health care research, and have the resources to do that and make a difference.”

There is a sense of abundance in Bair’s summary of her personal experience of MIT. “I learned that while a single-minded focus was good to get me into MIT, I needed to expand once I got here.” She joined the Kappa Alpha Theta sorority and played a leadership role in it. She thrived during two summer internships: the first in mobile web development at The New York Times, the second at a tech startup in San Francisco that connects cancer patients with access to clinical trials.

“MIT pushed me in ways that I never imagined, and that has made me the person I am today,” she says. “MIT made me realize that real learning is about more than technical problems. The impact of this place comes with the conversations and experiences and knowing so many people who are doing interesting things.”

She smiles at the contrast between who she believed herself to be when she arrived at MIT in the fall of 2014, and who she has become. “You get this feeling of cutting-edge stuff going on here. It changes you. I could never imagine myself as anything but a doctor when I was in Michigan. Now look at me. I’ve become a real computer science nerd. And I’m cool with it.”

 

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Wednesday, June 6, 2018 - 5:15pm

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Annamarie Bair, a premed student turned computer science major, is drawn to the promise of artificial intelligence and health care.

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At MIT doctoral hooding ceremony, a call to make the world 'more just, more fair'

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Candis Callison urged new graduates to use their doctoral degrees to make a difference. Photo: Dominick Reuter

Editor's Note: Photos from the EECS reception following the MIT hooding ceremony will be coming soon.

 

Professor and journalist Candis Callison SM ’02 PhD ’10 urged MIT’s doctoral graduates to “make the world a more just, more fair place,” in her keynote speech today at the Institute’s colorful 2018 Investiture of Doctoral Hoods.

“The contributions you can make with your PhD can amplify some kinds of data, collaborations, problems, and solutions over others,” said Callison, a scholar at the University of British Columbia and award-winning journalist. “Should you choose, your work and your research can shift society toward better systems and processes, which make the world a more just, more fair place for all of us to live in.”

The joyous ceremony celebrates new graduates earning doctoral degrees this academic year. It was held in MIT’s Johnson Athletics Center, where a large audience of family members and friends filled the stands.

MIT professors, clad in the visually brilliant, multihued robes of the universities where they received their own doctorates — including MIT — placed doctoral hoods over students from 26 departments, programs, and centers at the Institute, as well as MIT’s joint program with the Woods Hole Oceanographic Institution.

In all, MIT awarded 645 doctoral degrees in the 2017-2018 academic year, including 107 in EECS.

With most of those graduates in attendance, Callison offered a welcoming sentence — translated as “I am happy for what you’ve all done” — in the language of the Tahltan Nation, an indigenous people of British Columbia, of which she is a member. The audience then repeated the greeting along with her.

In her remarks, Callison reflected on the culture of MIT as well as her own experiences as a doctoral student at the Institute.

“MIT is a place that values not only experimental methods and outcomes in research, but an experimental life,” Callison said, adding that this can include “working hard, taking detours and risks, becoming resilient when things don’t go as planned, taking the scenic route through failures and innovative efforts to define and solve problems.”

She suggested that “there are very few, if any other places, that I think would have had faculty that supported me to do my coursework and research the way I did.”

Callison began her career as a journalist for the Canadian Broadcasting Corporation and CTV News. After eight years in television, she arrived at MIT, where she first pursued a master’s degree in the Comparative Media Studies program, something she termed “an incredible experience.” She then earned her PhD in 2010 from the HASTS program, the joint doctoral group comprising MIT History faculty, the program in Anthropology, and the program in Science, Technology, and Society.

Callison’s doctoral thesis examined the ways knowledge about climate change relates to the social groups in which people live; that PhD research also formed the basis of her 2014 book, “How Climate Change Comes to Matter: The Communal Facts of Life,” published by Duke University Press. Callison is currently an associate professor at the University of British Columbia.

As Callison recounted, she also had two children while a PhD student at MIT — “just in case you thought I was joking about leading an experimental life” — which certainly presented challenges when it came to finishing her degree. And, while she noted that “it takes a lot of mettle to succeed” in doctoral studies at MIT, “having a community of others doing what you’re doing really helps.”

Callison also observed that obtaining a PhD at MIT both amplifies the values and ideas that students bring with them to graduate school, and provides them with tools to be used subsequently, at all stages of life.

“I’ve come to think of my time here as one of the best and most formative parts of my journey,” Callison observed, adding: “It’s neither a beginning nor an end.”

Callison was introduced by MIT Chancellor Cynthia Barnhart SM ’86, PhD ’88, the Ford Foundation Professor of Engineering, who also briefly addressed the graduates.

“You have made discoveries and created knowledge at a time when society faces grand challenges and urgently needs more understanding, more innovation, and more problem-solving,” Barnhart said, adding that the faculty “feel fortunate to stand with you in applying ‘mens et manus et cor,’ mind and hand and heart, toward building a better world.” 

Barnhart also quipped that the ceremony represented a moment of “accomplishment, elation, hope, and, let’s be honest, of relief” for the new doctorate holders, after years of concerted study.

The current format of MIT’s doctoral hooding ceremony represents the revitalization of an venerable tradition. Callison’s speech in 2018 marks the fourth year the ceremony has had a keynote speaker (who thus far has always had an MIT doctorate). Callison was chosen with input from MIT faculty and doctoral students.

The colorful academic regalia of the doctoral ceremony represents an evolving tradition as well. Academic regalia dates at least to the 15th century, but American universities did not codify the standards of graduation gowns and hoods until 1893.

At MIT, doctoral degree robes have featured their current design since 1995. MIT gowns have a silver-gray robe with a striking cardinal red velvet front panel, as well as cardinal red velvet bars on the sleeves. There are additional color markings denoting whether graduates have received a Doctor of Philosophy (PhD) or a Doctor of Science (ScD) degree.

The doctoral hoods themselves are part of the doctoral robe ensemble. After the welcoming remarks by Barnhart and the keynote address by Callison, all doctoral graduates had their names announced as they walked across the stage individually. The new doctoral degree holders then had the hoods draped over their shoulder by their department or program heads.

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Thursday, June 7, 2018 - 2:45pm

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Congratulations, EECS doctoral graduates!

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EECS reception, June 7, 2018. Photo: Gretchen Ertl

 

EECS awarded hoods to more than 100 doctoral graduates in a ceremony on June 7, 2018.

See more coverage and photos from the event on the  MIT News website. Additional coverage and photos from MIT's commencement ceremony on June 8 will be coming shortly.

 

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Thursday, June 7, 2018 - 9:00pm

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The traditional "cap toss" was a highlight of the EECS reception following the Investiture of Doctoral Hoods.

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Facebook COO Sheryl Sandberg tells urges 2018 MIT graduates to be 'clear-eyed optimists'

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Addressing the MIT Class of 2018, Facebook COO Sheryl Sandberg said, “the most difficult problems and the greatest opportunities are not technical, they are human." Photo: Dominick Reuter

David Chandler | MIT News

 

When MIT Commencement speaker and Facebook Chief Operating Officer Sheryl Sandberg asked the 999 undergraduates and 1,821 graduate students who were about to receive their degrees to raise their hands if they knew exactly what they wanted to do for a career, quite a few hands shot up.

“That’s impressive,” she said, speaking during a sunny ceremony on June 8 in Killian Court. “I did not.” In fact, as she recalled, she went through quite a few different kinds of jobs and was sure of just one thing: She didn’t want to go into business or technology.

“Things won’t always end up as you think,” she said. “But you will gain valuable lessons along life’s uncertain path.” She described one such lesson that she learned in her very first job after graduation, working in a leprosy treatment center in India.

Technically, the problem of leprosy had already been solved, she said. The disease can be easily diagnosed and is totally curable now, yet the age-old stigma attached to the disease remained, and many patients hid themselves from view rather than seeking care. The needed breakthrough came not just from medical technology, but from community leaders, she said.

“They wrote plays and songs in local languages and went around the community convincing those suffering to come forward without fear,” Sandberg said. “They understood that the most difficult problems and the greatest opportunities are not technical, they are human. In other words, it’s not just about technology, it’s about people.”

She noted that “today, anyone with an internet connection can inspire millions with a single sentence or a single image. That gives extraordinary power to those who use it to do good — to march for equality, reignite the movement against sexual harassment, rally around the things they care about and the people they need to be there for.” But, she said, “it also empowers those who seek to do harm.”

That leaves three options, she said: retreat in fear, barrel forward anyway, or take another choice. “I encourage you to choose the third option — to be clear-eyed optimists, to see that building technology that supports equality, democracy, truth, and kindness means looking around corners and throwing up every possible roadblock against hate, violence, and deception.”

Sandberg, whose company has increasingly faced criticism over the sharing of its users’ personal information, addressed that contentious issue head on. “At Facebook, we didn’t see all the risks coming, and we didn’t do enough to stop them,” she said. Recalling advice from a naval officer, that calm seas never make good sailors, she said: “When you own your mistakes, you can work harder to correct them — and even harder to prevent the next ones. That’s my job now.”

And it’s also the job of “all of us here,” she said. “It’s not enough to be technologists —we have to make sure that technology serves people.”

MIT President L. Rafael Reif, in his charge to the class of 2018, compared the students’ work at the Institute to the training of Olympic athletes — among whom, to the surprise of many, there have been almost as many MIT graduates as there have been Nobel laureates (36 Nobelists and 35 Olympians over the years).

Among the similarities, he said, are the need to be fearless in pursuing goals, and the experience of working with people from every corner of the world. And, he added, the fact that what they do will “raise the bar for everyone who comes after.”

Reif cited many specific initiatives by members of this student class, including the project to support each other by asking “tell me about your day,” efforts to help students who struggle to pay for food, and recommendations for ways to make the Institute more caring, welcoming, and inclusive.

He concluded by emphasizing a very important difference between MIT and the Olympics: “At MIT, in order for you to win, no one has to lose. No one even has to come in second!” That’s because, he said, “we are members of a single team — united with a single mission.”

In essence, that mission comes down to trying to “fix things that are broken … to hack the world, and at least to try to heal the world too.” He urged the graduates to “find your calling. Solve the unsolveable. Invent the future. Take the high road.”

Sarah Ann Goodman, president of the Graduate Student Council, told the graduates about her own research using electron microscopy, and how in that work it is essential to get multiple views of a sample from different angles. In the same way, she said, “when we tackle global challenges such as health care access, climate change, and human rights issues, I hope we ask ourselves — are all perspectives being considered? Whose voices are not being heard? ... How do we create an inclusive environment that not only keeps everyone at the table, but elevates everyone at the table?”

Colin Webb, president of the graduating senior class, spoke of the great diversity of students that he had come to know in his time at MIT, and even offered brief comments in several different languages. “In order to change the world, we must first understand the world’s wide variety of people and backgrounds. Because people are the root of all the challenges we aim to solve, and we look to each other, other people, when we search for solutions.”

Webb added that “To me it’s quite clear that MIT is the place that makes the magic happen. It’s the place where I can graduate today and know that I’m going to make an impact tomorrow.”

As Sandberg concluded in her remarks to the MIT graduates of 2018, “I hope you will use your influence to make sure technology is a force for good in the world. Technology needs a human heartbeat; the things that bring us together and that bring us joy are the things that matter most.”

For additional Commencement content, along with a slideshow and video, please visit the MIT News website.

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Friday, June 8, 2018 - 4:45pm

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MIT President L. Rafael Reif's charge to the Class of 2018

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MIT President L. Rafael Reif urged graduates to "invent the future." Photo: Dominick Reuter

MIT News Office

 

Following is the prepared text of the charge to the graduates by MIT President L. Rafael Reif for the Institute’s 2018 Commencement, held June 8, 2018.

It is great to have all of you here on Killian Court, on this wonderful day, for this tremendously important occasion.

But first, I have a question for today’s graduates: Would you remember if I asked you where you were this past February 15th? Probably not. In fact, on this wonderful June morning, it may seem a little cruel to make you think about February at all! But I do, because this year, on February 15th, one member of our extended community was doing something very specific and memorable.

In a very cold spot in South Korea, Adam Edelman, MIT Class of 2014, was becoming the first MIT graduate in 10 years to compete in the Olympics.

Now, think about this for a moment: Which do you think would be larger, the number of MIT graduates who have ever competed in, or qualified for, the Olympics — or the number of our alumni who have won the Nobel Prize?

Remember, this is MIT…

Well, it turns out that 36 MIT graduates are Nobel Laureates. But 35 MIT graduates have taken part in the Olympic Games! They have represented 28 nations, in 11 sports — from rowing and wrestling, to sailing, fencing, and rifle (And we’re still waiting for “Pirate” to qualify as an Olympic event. I think they are afraid we’d take all the medals!)

Olympic glory may not be the first thing people associate with MIT, but I believe the experience of these exceptional athletes has some fascinating similarities to what you’ve learned here.

One obvious connection between Olympic athletes and MIT graduates is that you are all trained to be fearless.

For instance, Adam’s sport is pretty unusual. It’s called “skeleton.” (Yes, skeleton!) As he describes it, it’s like “taking a lunch tray, diving headfirst onto it and going about 90 miles an hour down an icy chute.”

Now, as those who’ve taken physics here already know, that may sound frightening. But, as Adam might tell you, it’s nothing compared to your first test in 8.01!

In your time at MIT, you have moved faster, stretched farther and accomplished more than you ever thought possible. And sometimes the chute was pretty steep! So, as you step out into the world, remember that you carry within you the deep confidence that you have earned: The confidence that you know how to face, and overcome, difficult challenges. (And, by the way, the fearlessness you learned here will set you apart — even if you forget to wear your brass rat!)

Here in our “Olympic-Village-on-the-Charles,” you’ve also experienced the thrill of working and playing with people from every corner of the Earth. The people of MIT do speak dozens of different languages. But — just like Olympians — we also speak a great shared language of measurement and numbers and facts.

At the Olympics, the fact is there’s only one way to get a medal. And there’s only one way to get an MIT degree: The hard way! (Let me ask our 50th Reunion class: Did I get that right? Is that the MIT you remember?)

There’s one more Olympic connection that says something important about you — this specific class of new MIT graduates:

At the Olympics, some people raise the bar for everyone who comes after. Similarly, those of you who leave us today have set a very important new standard.

Individually and together, you helped us see that, if we truly aspire to make a better world, we also need to make a better MIT. And then, through your compassion, creativity and leadership — and your magnificent example — you showed us how to do precisely that. For instance:

  • By invoking the simple words, “Tell Me About Your Day,” you inspired all of us to perform everyday miracles of human connection. Izzy, wherever you are seated, thank you!
  • You discovered that some students on our campus don’t always know how they’ll pay for their next meal and you helped us find practical ways to help.
  • You developed serious, constructive recommendations for making MIT more caring, welcoming, and inclusive — and you persisted in driving that change.
  • When federal tax changes threatened to make graduate student education unaffordable, you came together to make your voices heard on Capitol Hill — and you won!
  • When members of our community were prevented from returning by the federal travel ban, you came together to try every angle, to help make sure they could come back to join us. (And I’m delighted that Niki Mossafer-Rahmati is graduating here today!)
  • And when, as a community, we most needed to talk with each other, despite our differences, you wrapped in paper the great pillars of our Main Lobby, so we could share our thoughts. And with that gesture, you wrapped this complex community together with the bonds of patient listening, and mutual respect, and love.

 

In short, in these and many other ways, you made MIT better. And I thank you! It makes me proud that you have set this new standard of community for MIT. And it makes me certain that you will make a better world.

I tried to make the case that MIT has some important things in common with the Olympics.

But I want to highlight one very important difference.

At MIT, in order for you to win, no one has to lose. No one even has to come in second! That’s because in our Olympic Village, we are members of a single-team, united with a single-mission. And we strive to see the world, not as a “zero-sum” game, but as “positive sum” — as a world where generous collaboration makes each collaborator smarter, stronger, and richer in every way.

This deep shared world-view gives me the confidence to deliver my charge to you.

Now, I’m going to use a word that feels very comfortable at MIT, although it has taken on a troubling new meaning elsewhere. But I know that our graduates will know what I mean.

After you depart for your new destinations, I want to ask you to hack the world — until you make the world a little more like MIT: More daring and more passionate. More rigorous, inventive and ambitious. More humble, more respectful, more generous, more kind.

And because the people of MIT also like to fix things that are broken, as you strive to hack the world, please try to heal the world, too. Our society is like a big, complicated family, in the midst of a terrible argument. I believe that one way to make it better is to find ways to listen to each other, to understand our differences, and to work constantly to remind each other of our common humanity. I know you will find your own ways to help with this healing, too.

This morning, I see more than 2,800 new graduates, who are ready for this urgent and timeless problem set. You came to MIT with exceptional qualities of your own. And now, after years of focused and intense dedication, you leave us, equipped with a distinctive set of skills, and steeped in this community’s deepest values: A commitment to excellence. Integrity. Meritocracy. Boldness. Humility. An open spirit of collaboration. A strong desire to make a positive impact. And a sense of responsibility to make the world a better place.

So now, go out there. Join the world. Find your calling. Solve the unsolvable. Invent the future. Take the high road. And you will continue to make your family, including your MIT family, proud.

On this wonderful day, I am proud of all of you. To every one of the members of the graduating Class of 2018: Please accept my best wishes for a happy and successful life and career. Congratulations!

Other Commencement content: In her Commencement address, Facebook COO Sheryl Sandbook urged graduates "to be clear-eyed optimists." For additional Commencement coverage, visit the MIT News website.

 

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Friday, June 8, 2018 - 5:15pm

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Reif urges graduates to “find your calling. Solve the unsolvable. Invent the future. Take the high road.”

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MIT announces leadership of its Quest for Intelligence

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EECS Professor Antonio Torralba                                                               Photo: Lillie Paquette, School of Engineering

MIT News

Antonio Torralba, a member of the EECS faculty, has been named the inaugural director of the MIT Quest for Intelligence, effective immediately, Provost Martin Schmidt announced in an email to the MIT community.

Launched on February 1 of this year, The Quest is a campus-wide initiative to discover the foundations of intelligence and to drive the development of technological tools that can positively influence virtually every aspect of society.

“The range of questions we aspire to explore through The Quest is simply breathtaking,” says MIT President L. Rafael Reif. “There are moments in the history of science when the tools, the data, and the big questions are perfectly synchronized to achieve major advances. I believe we are in just such a moment, and that we are poised to advance the understanding of intelligence in every sense in a profound way. Antonio is exactly the leader we need to move this effort forward.”

An expert in computer vision, machine learning, and human visual perception, Torralba is also the MIT director of the MIT­–IBM Watson AI Lab, and a principal investigator at the Computer Science and Artificial Intelligence Laboratory (CSAIL).

“The Quest is fundamentally a collaboration, so we are excited to watch Antonio build on the success he has already had with the MIT­–IBM Watson AI Lab,” Schmidt wrote. “Along with the vision and insight he shows in his research, he has remarkable talents as a convener of people and as an enabler of connections.”

Given The Quest’s scale and the breadth of its ambition, Schmidt has also established a robust leadership team to work with Torralba in furthering the initiative’s goals.

Aude Oliva, a principal research scientist at CSAIL and the MIT executive director at the MIT–IBM Watson AI Lab, will serve as The Quest’s executive director.

James DiCarlo, the Peter de Florez Professor of Neuroscience, head of the Department of Brain and Cognitive Sciences, and principal investigator at the McGovern Institute, will be director of “The Core.” One of The Quest’s two linked entities, The Core will advance the science and engineering of both human and machine intelligence. Daniela Rus, the Andrew (1956) and Erna Viterbi Professor of EECS and director of CSAIL, will be associate director of The Core.  

The Core’s scientific directors will be Josh Tenenbaum, professor of computational cognitive science, a research thrust leader at the Center for Brains, Minds and Machines, and a member of CSAIL; and Leslie Kaelbling, the Panasonic Professor of Computer Science and Engineering and a member of CSAIL. The Core’s founding scientific advisor will be Tomaso Poggio, the Eugene McDermott Professor of Brain and Cognitive Sciences, director of the Center for Brains, Minds and Machines, a member of CSAIL, and principal investigator at the McGovern Institute. Together, the leadership of The Core will bring together teams of researchers to tackle the most ambitious “moonshot” projects focusing on the science and engineering of intelligence.  

Nicholas Roy, professor of aeronautics and astronautics and a member of CSAIL, will be the director of The Quest’s second linked entity, “The Bridge.” Dedicated to the application of MIT discoveries in natural and artificial intelligence to all disciplines, The Bridge will host state-of-the-art tools from industry and research labs worldwide. The Bridge’s associate director of strategic initiatives will be Cynthia Breazeal, an associate professor of media arts and sciences at the Media Lab. Roy and Breazeal will work with faculty from across MIT to ensure the discoveries and developments facilitated by The Quest have an impact, both within and beyond academic research.

“I would like to extend my deep appreciation to this new leadership team, and to the many faculty who have helped us get this remarkable initiative off to such a powerful start,” Schmidt wrote. “We look forward to the advances and discoveries that are yet to come as we embark on The Quest.”

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Monday, June 11, 2018 - 4:30pm

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EECS Professor Antonio Torralba has been named inaugural director of the new initiative. Other EECS faculty members will play major roles as well.

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Artificial intelligence senses people through walls

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Image: Jason Dorfman/MIT CSAIL

 

X-ray vision has long seemed like a far-fetched sci-fi fantasy. But over the last decade a team led by Dina Katabi, the Andrew & Erna Viterbi Professor of EECS and a member of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), has continually gotten us closer to seeing through walls.

The team's latest project, “RF-Pose,” uses artificial intelligence (AI) to teach wireless devices to sense people’s postures and movement, even from the other side of a wall.

The researchers use a neural network to analyze radio signals that bounce off people’s bodies, and can then create a dynamic stick figure that walks, stops, sits, and moves its limbs as the person performs those actions.

The team says that RF-Pose could be used to monitor diseases like Parkinson’s, multiple sclerosis (MS), and muscular dystrophy, providing a better understanding of disease progression and allowing doctors to adjust medications accordingly. It could also help elderly people live more independently, while providing the added security of monitoring for falls, injuries and changes in activity patterns. The team is currently working with doctors to explore RF-Pose’s applications in health care.

All data the team collected has subjects' consent and is anonymized and encrypted to protect user privacy. For future real-world applications, they plans to implement a “consent mechanism” in which the person who installs the device is cued to do a specific set of movements in order for it to begin to monitor the environment.

“We’ve seen that monitoring patients’ walking speed and ability to do basic activities on their own gives health care providers a window into their lives that they didn’t have before, which could be meaningful for a whole range of diseases,” says Katabi, who co-wrote a new paper about the project. “A key advantage of our approach is that patients do not have to wear sensors or remember to charge their devices.”

Besides health care, the team says that RF-Pose could also be used for new classes of video games where players move around the house, or even in search-and-rescue missions to help locate survivors.

Katabi co-wrote the new paper with PhD student and lead author Mingmin Zhao, EECS Professor Antonio Torralba, postdoc Mohammad Abu Alsheikh, graduate student Tianhong Li, and PhD students Yonglong Tian and Hang Zhao. They will present it later this month at the Conference on Computer Vision and Pattern Recognition (CVPR) in Salt Lake City, Utah.

One challenge the researchers had to address is that most neural networks are trained using data labeled by hand. A neural network trained to identify cats, for example, requires that people look at a big dataset of images and label each one as either “cat” or “not cat.” Radio signals, meanwhile, can’t be easily labeled by humans.

To address this, the researchers collected examples using both their wireless device and a camera. They gathered thousands of images of people doing activities like walking, talking, sitting, opening doors and waiting for elevators.

They then used these images from the camera to extract the stick figures, which they showed to the neural network along with the corresponding radio signal. This combination of examples enabled the system to learn the association between the radio signal and the stick figures of the people in the scene.

Post-training, RF-Pose was able to estimate a person’s posture and movements without cameras, using only the wireless reflections that bounce off people’s bodies.

Since cameras can’t see through walls, the network was never explicitly trained on data from the other side of a wall – which is what made it particularly surprising to the MIT team that the network could generalize its knowledge to be able to handle through-wall movement.

“If you think of the computer vision system as the teacher, this is a truly fascinating example of the student outperforming the teacher,” says Torralba.

Besides sensing movement, the authors also showed that they could use wireless signals to accurately identify somebody 83 percent of the time out of a line-up of 100 individuals. This ability could be particularly useful for the application of search-and-rescue operations, when it may be helpful to know the identity of specific people.

For this paper, the model outputs a 2-D stick figure, but the team is also working to create 3-D representations that would be able to reflect even smaller micromovements. For example, it might be able to see if an older person’s hands are shaking regularly enough that they may want to get a check-up.

“By using this combination of visual data and AI to see through walls, we can enable better scene understanding and smarter environments to live safer, more productive lives,” says Zhao.

For more information on this story, including a video, visit the MIT News website.
 

Date Posted: 

Tuesday, June 12, 2018 - 5:30pm

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The wireless smart-home system from the Computer Science and Artificial Intelligence Laboratory could monitor diseases and help the elderly “age in place.”

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