In a world where hackers can sabotage power plants and impact elections, there has never been a more crucial time to examine cybersecurity for critical infrastructure, most of which is privately owned.

According to MIT experts, over the last 25 years presidents from both parties have paid lip service to the topic while doing little about it, leading to a series of short-term fixes they liken to a losing game of “Whac-a-Mole.” This scattershot approach, they say, endangers national security.

In a new report based on a year of workshops with leaders from industry and government, the MIT team has made a series of recommendations for the Trump administration to develop a coherent cybersecurity plan that coordinates efforts across departments, encourages investment, and removes parts of key infrastructure like the electric grid from the internet.

Coming on the heels of a leak of the new administration’s proposed executive order on cybersecurity, the report also recommends changes in tax law and regulations to incentivize private companies to improve the security of their critical infrastructure. While the administration is focused on federal systems, the MIT team aimed to address what’s left out of that effort: privately-owned critical infrastructure.

“The nation will require a coordinated, multi-year effort to address deep strategic weaknesses in the architecture of critical systems, in how those systems are operated, and in the devices that connect to them,” the authors write. “But we must begin now. Our goal is action, both immediate and long-term.”

Entitled “Making America Safer: Toward a More Secure Network Environment for Critical Sectors,” the 50-page report outlines seven strategic challenges that would greatly reduce the risks from cyber attacks in the sectors of electricity, finance, communications and oil/natural gas. The workshops included representatives from major companies from each sector, and focused on recommendations related to immediate incentives, long-term research and streamlined regulation.

The report was published by MIT’s Internet Policy Research Initiative (IPRI) at the Computer Science and Artificial Intelligence Laboratory (CSAIL), in conjunction with MIT’s Center for International Studies (CIS). Principal author Joel Brenner was formerly inspector general of the National Security Agency and head of U.S. counterintelligence in the Office of the Director of National Intelligence. Other contributors include Hal Abelson, David Clark, Shirley Hung, Kenneth Oye, Richard Samuels, John Tirman and Daniel Weitzner.

To determine what a better security environment would look like, the researchers convened a series of workshops aimed at going beyond the day-to-day tactical challenges to look at deep cyber vulnerabilities.

The workshops highlighted the difficulty of quantifying the level of risk across different sectors and the return on investment for specific cybersecurity measures. In light of facility-directed attacks like the Stuxnet virus and the sabotage of a Saudi oil refinery, attendees expressed deep concern about the security of infrastructure like the electric grid, which depends on public networks.

“Connecting [these operations] to the Internet has brought undoubted efficiencies to electricity generators and other industries, but it has also created dangerous vulnerabilities in the systems that keep the lights on and power the economy,” the MIT team writes, echoing concerns that were raised in a Department of Energy report published in January.

Brenner and his colleagues also contend that the technical challenges could actually be easier to address than the legal and economic ones. To align incentives with better security, they call for tax and regulatory policy that rewards cybersecurity investment, including investment to convert to a more secure Domain Name System (DNS) for websites.

The authors are optimistic that President Trump’s team will be receptive to the report, given the shared desire to fix America’s vulnerable infrastructure. “Our recommendations complement their attention to federal systems,” Brenner says. “Our current cyber insecurity is a national disgrace, and we must defend the networks that the safety of our nation depends on.”

Two EECS faculty members and a historic alumna are included in a new micro-documentary series, "Storied Women of MIT."

MIT Video Productions (MVP) created the series to spotlight remarkable women from MIT’s past and present, releasing the 60-second videos throughout March 2017 to mark Women's History Month. Among those featured in the series were:

• Mildred Dresselhaus, Institute Professor Emerita of Physics and Electrical Engineering and Computer Science, widely known as "the queen of carbon science.” (For more on Dresselhaus, who passed away in February 2017 at age 86, see this MIT News tribute.)
   
• Dina Katabi SM ’99, PhD ’03, Andrew & Erna Viterbi Professor of Electrical Engineering and Computer Science, a specialist in wireless and mobile networks.
   
• Li Fu Lee’29, the first Chinese woman to attend MIT and among the first women to receive an electrical engineering degree.
   

You may view the entire series on MIT's Teaching Excellence website or on YouTube.

Please join us for Masterworks, the EECS's annual poster presentation, demos, and celebration of thesis research leading to the degrees of Master of Science (SM) and Master of Engineering (MEng). EECS faculty members will evaluate the posters and presentations to determine the awardee for the 2017 Morris Joseph Levin Award for Outstanding Masterworks Thesis Presentation. In addition, several other prizes will be drawn from among the participants.

Tuesday, April 18, 2017 (4-6 pm)

Immediately following EECScon

Samberg Conference Center
Chang Building (E52) map
50 Memorial Drive

Refreshments will also be served during the event. 

Student Registration

Student Poster Upload

Industry Registration

Questions?  Write to eecs-masterworks@mit.edu

Daniela Rus, director of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) has received the Engelberger Robotics Award in recognition of her pioneering work as a researcher, innovator, and educator in robotics. The Robotic Industries Association (RIA), a trade organization, presented the award recently in conjunction with the Automate 2017 Exhibition and Conference and the International Symposium on Robotics in Chicago.

Rus, who is a professor of computer science and electrical engineering, heads the Distributed Research Lab, which develops robotic technologies, including robots that can garden, bake cookies from scratch, dance with humans, and fly to conduct surveillance without human assistance. The lab has also worked on self-driving golf carts, wheelchairs, scooters, and city cars designed to reduce traffic deaths and provide new mobility options for elderly peoople. Companies such as iRobot and Boeing have commercialized innovations drawn from Rus' research.

The award is named for Joseph F. Engelberger, founder and president of Unimation, Inc., the world's first industrial robot manufacturer. It is “presented to individuals for excellence in technology development, application, education, and leadership in the robotics industry,” according to the RIA. Nearly 125 robotics leaders from 17 nations have received the awards since their inception in 1977.

This year's other Engleberger Robotics Award winner, Gill Pratt, has strong ties to MIT. As CEO of the Toyota Research Institute, Pratt also works toward developing safer, and self-driving, cars. Previously, he was an MIT associate professor of electrical engineering and computer science. He also received three academic degrees from MIT: a bachelor's in computer science and engineering, and a master's degree and PhD, both in electrical engineering and computer science.

"Dr Pratt and Dr. Rus are known throughout the world for their outstanding contributions to the robotics industry," RIA President Jeff Burnstein noted in announcing the awards.

At the EECS Celebrates event, department leaders present awards to outstanding students, faculty, and staff. Invitations have been sent out for the 2017 event, to be held on May 21 at the Museum of Science in Boston.

Here you can see photos and details from EECS Celebrates 2016.  EECS honored the Department's award recipients for the 2015-2016 academic year in a ceremony at the Museum of Fine Arts, Boston on Sunday, May 15. Click below to scroll through photos of the event. All images are courtesy of Gretchen Ertl and the MFA. 

The 2016 award winners were: 

EECS Faculty Research Innovation Fellowship
Manolis Kellis

Frank Quick Faculty Research Innovation Fellowship
Jongyoon Han
Polina Golland

Louis D. Smullin ('39) Award for Teaching Excellence
Thomas Heldt

Jerome H. Saltzer Award
Yury Polyanskiy

Burgess ('52) & Elizabeth Jamieson Award for Excellence in Teaching
Regina Barzilay
Samuel Madden

Ruth and Joel Spira Teaching Award
Luca Daniel
Vinod Vaikuntanathan

EECS Outstanding Educator Award
Katrina LaCurts

StartMIT Competition First Place
De-Ice team: Alexandru Bratianu-Badea, Ruben Toubiana, Jelena Stojakovic, Hayden K. Cornwell

StartMIT Competition Runner Up
Steph Speirs

Paul L. Penfield Student Service Award
Pratheek Nagaraj
Joel Jean

Carlton E. Tucker Teaching Award
Jessica Noss

Harold L. Hazen Teaching Award
Ilia A. Lebedev

Frederick C. Hennie III Teaching Award
Atulya Yellepeddi
Tarek A. Lahlou
Jonathan D. Terry
Harihar G. Subramanyam

Undergraduate Teaching Assistant (UTA) Award
Austin J. Liew
Ethan C. Payne

SuperUROP TA Award
Zoya Bylinskii

Jeremy Gerstle UROP Award
Eric C. Chen
Fernando A. Yordan
Project: 3-D Arm Reconstruction for Lymphedema Detection
Supervisor: Regina Barzilay

Morais (1986) and Rosenblum (1986) Award
Rachel Devlin
Eric Ponce
Project: Practical Magic
Supervisor: Steve Leeb

Anna Pogosyants UROP Award
Hayke Saribekyan
Project: Big Data Agglomeration for Connectomics
Supervisor: Nir Shavit

Lidlicker UROP Award
Ian M. Reynolds
Project: Human Echolocation in a Wearable Mobility
Supervisory: Aude Oliva

SuperUROP Outstanding Research Project Award
Julia Belk
Project: Control of DC Electrical Networks to Enable Peer-to-Peer Energy Sharing
Supervisor: David Perreault

SuperUROP Outstanding Research Project Award
Damon Doucet
Project: Creating a Compiler Instrumentation Framework
Supervisor: Charles Leiserson

SuperUROP Technical Report Award
Tally E. Portnoi
Project: Lipid Suppression for Magnetic Resonance Spectroscopic Imaging of Infants: Improving Lipid-Basis Penalty Reconstruction with Multiple-TE Acquisition
Supervisor: Elfar Adalsteinsson

SuperUROP Technical Report Award
Nischal Bhandari
Project: Plane-Based Depth Image Completion
Supervisor: John Fisher

SuperUROP Technical Report Award
Alyssa P. Cartwright
Project: Optical Control of Engineered Mammalian Cells
Supervisor: Rajeev Ram

Northern Telecom/BNR Project Award Best 6.111 Project
Samuel M. Jacobs
Valerie Y. Sarge
Project: Surfing on a Sine Wave

Northern Telecom/BNR Project Award Best 6.111 Project
Kevin S. Chan
David J. Gomez
Battushig Myanganbayar
Project: Autonomous RC Car

George C. Newton Undergraduate Laboratory Prize: 6.111
Yanni E. Caroneos
Valentina I. Chamorro
Project: A DSP Audio PreAmplifier

David A. Chanen Writing Award for writing in 6.033
Dustin Doss
Project: Critique 2: MapReduce

Morris Joseph Levin Award Masterworks Thesis Presentation
Curtis Northcutt
Project: Detecting and Preventing "Multiple-Account" Cheating in Massice Open Online Courses
Supervisor: Isaac Chuang

Morris Joseph Levin Award Masterworks Thesis Presentation
Preet Garcha
Project: Fully Integrated Therman Energy Harvesting System to Start up at 20 mV
Supervisor: Anantha Chandrakasan

Charles & Jennifer Johnson CS MEng Thesis First Place
Jeevana Priya Inala
Project: Synthesis of Domain Specific CNF Encoders for Bit-Vector Solvers
Supervisor: Armando Solar-Lezama

Charles & Jennifer Johnson CS MEng Thesis Second Place
Casey M. O'Brien
Project: Solving ANTS with Loneliness Detection and Constant Memory
Supervisor: Nancy Lynch

David Adler EE MEng Thesis Award
Max H. Dunitz
Project: Predicting Hyperlactatemia in the ICU
Supervisors: Thomas Heldt, George Verghese

J. Francis Reintjes Excellence in VI-A Industrial Practice Award
Rebecca Kekelishvili
Faculty Advisor: Katrina LaCurts
Company Supervisor: Padmanabhan Iyer (NetApp)

ACM/IEEE Best Advisor Award
Bob Berwick

HKN Best Instructor Award
Katrina LaCurts

Richard J. Caloggero Award
Myron (Fletch) Freeman

Department Head Special Recognition Award
Lisa Bella
Kate Boison

Presentation from the cermony (all photos are courtesy of Gretchen Ertl and the Museum of Fine Arts, Boston)

Three students in the Department of Electrical Engineering and Computer Science were among the winners of the 2017 Lemelson-MIT Student Prizes, which are designed to honor the nation’s most inventive college students.

The prizes, presented by the Lemelson-MIT Program, honored the EECS students for their inventions in the “Use it!” category, which focuses on technology that can improve consumer devices.

Chandara Doshi and Tania Yu, both seniors in EECS, were part of MIT’s Team Tactile, the $10,000 Lemelson-MIT “Use it!” Undergraduate Team Winner. The six-member team developed Tactile, a portable device that converts text to braille in real time. The technology allows people who are visually impaired to take a picture of printed text, which is then transcribed to braille on a refreshable display. Other Team Tactile members include Grace Li, Jessica (Jialin) Shi, and Charlene Xia, all seniors in the Department of Mechanical Engineering (MechE), and Chen (Bonnie) Wang, a senior in the Department of Material Science and Engineering.

Apoorva Murarka, a PhD candidate in electrical engineering, was the $15,000 Lemelson-MIT “Use it!” Graduate Winner. Murarka developed a 125-nanometer-thick membrane—approximately one-thousandth the width of a human hair—to produce high-fidelity sound more efficiently. This technology can be applied to hearing aids, earphones, or other consumer electronic devices, resulting in superior sound quality and longer battery life. Murarka previously received bachelor's and master's degrees in electrical engineering from MIT.

Celebrating young inventors

The Lemelson-MIT Student Prize is a national collegiate invention prize program, supported by The Lemelson Foundation, which celebrates young inventors that have designed and built prototypes of inventions to solve social problems. For 2017, the Lemelson-MIT Program honored four undergraduate teams and five individual graduate inventors. “These students display the brilliance and hope of their generation,” said Dorothy Lemelson, Lemelson Foundation chair. “We are proud to recognize them for their achievements.” 

Students entered their technology-based inventions in “Use it!” and three other categories: “Cure it!” (for improving health care), “Drive it!” (for improving transportation), and “Eat it!” (for improving food or agriculture). Other 2017 Lemelson-MIT Student Prize winners from MIT included:

• Katy Olesnavage, a PhD candidate in MechE, was the $15,000 Lemelson-MIT “Cure it!” Graduate Winner. Olesnavage was honored for her efforts to design a better prosthetic foot.
• Tony Tao, a PhD candidate in the Department of Aeronautics and Astronautics, was the $15,000 Lemelson-MIT “Drive it!” Graduate Winner. Tao was recognized for developing a mid-air-deployable, folding drone and an adaptable aircraft manufacturing (AAM) architecture.
• Natasha Wright, a PhD candidate in MechE, was the $15,000 Lemelson-MIT “Eat it!” Graduate Winner. Wright was honored for her work on inventions to help provide affordable, safe, and better-quality drinking water.

The Lemelson-MIT Program also honored graduate students or undergraduate teams from Stanford University, the University of California Berkeley, the University of Iowa, and the University of Maryland.

Lemelson-MIT Student Prize applicants were evaluated by screening committees with expertise in the invention categories as well as by a national judging panel of industry leaders. Screeners and judges assessed entries on the breadth and depth of inventiveness and creativity, potential for societal benefit and economic commercial success, impact on community and environmental systems, and the candidates’ experience as role models for youth.

Students interested in applying for the 2018 Lemelson-MIT Student Prize can find more information on the Lemelson-MIT website.

Tommi Jaakkola, a professor of computer science and engineering, has been named as the inaugural holder of the Thomas Siebel Professorship in the Department of Electrical Engineering and Computer Science (EECS) and the Institute for Data, Systems, and Society (IDSS).

The appointment was announced by EECS Department Head Anantha Chandrakasan, Vannevar Bush Professor of EECS, and IDSS Director Munther A. Dahleh, William Coolidge Professor of EECS. “The appointment recognizes Professor Jaakkola's leadership in the area of machine learning and his outstanding mentorship and educational contributions,” Chandrakasan and Dahleh wrote in a message to EECS faculty. “Professor Jaakkola is internationally well-known in the fields of machine learning and natural language processing, as well as in computational biology. He is widely respected as an original researcher and has made high-impact contributions.”

The new professorship was established through the generous contribution of veteran software entrepreneur Thomas Siebel, Chairman and CEO of C3IoT. Siebel is well-known at MIT for having established the Siebel Scholars program, which annually provides support for 16 MIT graduate students (five in EECS, five in Biological Engineering, five in the MIT Sloan School of Management, and one in Energy Science).

At the core of Jaakkola’s research are inferential and estimation questions in complex modeling tasks, ranging from developing the underlying theory and associated algorithms to translating such advances into applications. He has been a leading contributor to developing distributed probabilistic inference algorithms from this field’s inception to its current state as a well-established area of research.

From the modeling point of view, Jaakkola’s work covers a broad spectrum of areas, from the interface between generative and discriminative modeling, rethinking modeling from the point of view of randomization and combinatorial optimization, to recovery questions associated with continuous embedding of objects. In natural language processing (NLP), his contributions solving hard combinatorial inference problems such as natural language parsing, developing deep convolutional representations of text, and reframing complex models to reveal interpretable rationales for prediction. Several of his papers have received best-paper awards at leading events. 

In addition, Jaakkola “has made outstanding educational contributions,” Chandrakasan and Dahleh noted. He established and oversaw the growth of the graduate machine learning course , teaching it for many years until Professor Leslie Kaelbling took it over for further development. Together with Professor Regina Barzilay, he developed the undergraduate machine learning course, which now enrolls more than 500 students per term. He modernized the advanced NLP course, again taught with Barzilay, from the point of view of neural approaches to NLP. In 2015, Jaakkola received the Jamieson Award for Excellence in Teaching in recognition of his educational contributions.

He has also made valuable professional contributions in his field and within EECS. He has held editorial positions on prestigious journals such as the Journal of Machine Learning Research and the Journal of Artificial Intelligence Research. He has also co-chaired or overseen areas of major conferences, including the Conference on Neural Information Processing Systems (NIPS), the Conference on Uncertainty in Artificial Intelligence (UAI), and the Conference on Artificial Intelligence and Statistics (AISTATS). He served for many years on the EECS Faculty Search Committee and has been a member of other committees as well. He has also contributed to the career paths of many students and postdocs that he has supervised and mentored at MIT. Former students and postdocs from his research group now hold positions in leading universities such as MIT, CMU, and UC Berkeley. 

As an affiliate member of IDSS, Jaakkola has been instrumental in both the hiring and recruitment of statistics faculty as well as the creation of programs in statistics. He has served on the IDSS Statistics Faculty Search Committee from the start, and worked with the IDSS Statistics PhD Committee to develop a proposal for a dual PhD degree. He is also a participant in the Statistics and Data Science MicroMasters.

Srini Devadas, the Edwin Sibley Webster Professor of Electrical Engineering and Computer Science (EECS), is the 2017 recipient of the IEEE W. Wallace McDowell Award from the IEEE Computer Society.

The award recognizes "outstanding recent theoretical, design, educational, practical, or other similar innovative contributions that fall within the scope of Computer Society interest," according to the organization. Presented in honor of McDowell, a long-time IBM engineer and executive (and MIT alumnus), the award is among computing's highest individual honors. 

Devadas, a principal investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL), has been an EECS faculty member since 1988. Previous EECS-affiliated winners include Tim Berners-Lee, the 3Com Founders Professor of Engineering in the School of Engineering with joint appointments in EECS and CSAIL, who won in 1996, and Fernando Corbato, professor of computer science and engineering, emeritus, who received the award in 1966. 

Meg Murphy | School of Engineering 
April 27, 2017

By Adam Conner-Simons | Rachel Gordon

We’ve long known that blood pressure, breathing, body temperature and pulse provide an important window into the complexities of human health. But a growing body of research suggests that another vital sign – how fast you walk – could be a better predictor of health issues like cognitive decline, falls, and even certain cardiac or pulmonary diseases.

Unfortunately, it’s hard to accurately monitor walking speed in a way that’s both continuous and unobtrusive. Professor Dina Katabi’s group at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has been working on the problem, and believes that the answer is to go wireless.

In a new paper, the team presents “WiGait,” a device that can measure the walking speed of multiple people with 95 to 99 percent accuracy using wireless signals.

The size of a small painting, the device can be placed on the wall of a person’s house and its signals emit roughly one-hundredth the amount of radiation of a standard cellphone. It builds on Katabi’s previous work on WiTrack, which analyzes wireless signals reflected off people’s bodies to measure a range of behaviors from breathing and falling to specific emotions. 

“By using in-home sensors, we can see trends in how walking speed changes over longer periods of time,” says lead author and PhD student Chen-Yu Hsu. “This can provide insight into whether someone should adjust their health regimen, whether that’s doing physical therapy or altering their medications.”

WiGait is also 85 to 99 percent accurate at measuring a person’s stride length, which could allow researchers to better understand conditions like Parkinson’s disease that are characterized by reduced step size.

Hsu and Katabi developed WiGait with CSAIL PhD student Zachary Kabelac and master’s student Rumen Hristov, alongside undergraduate Yuchen Liu from the Hong Kong University of Science and Technology, and Assistant Professor Christine Liu from the Boston University School of Medicine. The team will present their paper in May at ACM’s CHI Conference on Human Factors in Computing Systems in Colorado.  

How it works

Today, walking speed is measured by physical therapists or clinicians using a stopwatch. Wearables like FitBit can only roughly estimate speed based on step count, and GPS-enabled smartphones are similarly inaccurate and can’t work indoors. Cameras are intrusive and can only monitor one room. VICON motion tracking is the only method that’s comparably accurate to WiGate, but it is not widely available enough to be practical for monitoring day-to-day health changes.

Meanwhile, WiGait measures walking speed with a high level of granularity, without requiring that the person wear or carry a sensor. It does so by analyzing the surrounding wireless signals and their reflections off a person’s body. The CSAIL team’s algorithms can also distinguish walking from other movements, such as cleaning the kitchen or brushing one's teeth.

Katabi says the device could help reveal a wealth of important health information, particularly for the elderly. A change in walking speed, for example, could mean that the person has suffered an injury or is at an increased risk of falling. The system's feedback could even help the person determine if they should move to a different environment such as an assisted-living home.

“Many avoidable hospitalizations are related to issues like falls, congestive heart disease, or chronic obstructive pulmonary disease, which have all been shown to be correlated to gait speed,” Katabi says. “Reducing the number of hospitalizations, even by a small amount, could vastly improve health care costs.”

The team developed WiGait to be more privacy-minded than cameras, showing you as nothing more than a moving dot on a screen. In the future they hope to train it on people with walking impairments from Parkinson’s, Alzheimer’s or multiple sclerosis, to help physicians accurately track disease progression and adjust medications.

“The true novelty of this device is that it can map major metrics of health and behavior without any active engagement from the user, which is especially helpful for the cognitively impaired,” says Ipsit Vahia, a geriatric clinician at McLean Hospital and Harvard Medical School, who was not involved in the research. “Gait speed is a proxy indicator of many clinically important conditions, and down the line this could extend to measuring sleep patterns, respiratory rates, and other vital human behaviors.”

Join us at a one-hour open house to unveil the newly renovated EECS Student Lounge!

Please drop by 38-201 on Thursday, May 4, between 2:00 and 3:00 pm.

The space, which has been redesigned based on student input, features new furniture and equipment. Refreshments will be served. No RSVP required.

Sangeeta Bhatia

Trained as both a physician and engineer, Bhatia is a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science. Her laboratory is dedicated to leveraging miniaturization tools from the world of semiconductor manufacturing to impact human health. She has pioneered technologies for interfacing living cells with synthetic systems, enabling new applications in tissue regeneration, stem cell differentiation, medical diagnostics, and drug delivery. Her team has developed human microlivers that model human drug metabolism, liver disease, and interaction with pathogens. The group also develops nanoparticles and nanoporous materials that can be designed to study, diagnose, and treat cancer and other diseases.

Bhatia earned a bachelor’s degree from Brown University, a PhD from MIT, and an MD from Harvard University. She is also a Howard Hughes Medical Institute investigator, an affiliated faculty member of the Harvard Stem Cell Institute, an institute member of the Broad Institute, and a biomedical engineer at the Brigham and Women's Hospital. She is an elected member of the National Academy of Engineering, the American Academy of Arts and Sciences, and the National Academy of Inventors. Her many awards include the 2014 Lemelson-MIT Prize; the 20th Heinz Award for Technology, the Economy, and Employment; the David and Lucile Packard Fellowship; and the NSF CAREER Award.