The hottest subjects on campus

On an afternoon in early April, Tommi Jaakkola is pacing at the front of the vast auditorium that is 26-100. The chalkboards behind him are covered with equations. Jaakkola looks relaxed in a short-sleeved black shirt and jeans, and gestures to the board. “What is the answer here?” he asks the 500 MIT students before him. “If you answer, you get a chocolate. If nobody answers, I get one — because I knew the answer and you didn’t.” The room erupts in laugher.

With similar flair but a tighter focus on the first few rows of seats, Regina Barzilay had held the room the week prior. She paused often to ask: “Does this make sense?” If silence ensued, she warmly met the eyes of the students and reassured them: “It’s okay. It will come.” Barzilay acts as though she is teaching a small seminar rather than a stadium-sized class requiring four instructors, 15 teaching assistants, and, on occasion, an overflow room.

Welcome to “Introduction to Machine Learning,” a course in understanding how to give computers the ability to learn things

Analysis of laparoscopic procedures

Laparoscopy is a surgical technique in which a fiber-optic camera is inserted into a patient’s abdominal cavity to provide a video feed that guides the surgeon through a minimally invasive procedure.

Laparoscopic surgeries can take hours, and the video generated by the camera — the laparoscope — is often recorded. Those recordings contain a wealth of information that could be useful for training both medical providers and computer systems that would aid with surgery, but because reviewing them is so time consuming, they mostly sit idle.

Researchers at MIT and Massachusetts General Hospital hope to change that, with a new system that can efficiently search through hundreds of hours of video for events and visual features that correspond to a few training examples.

In work they presented at the International Conference on Robotics and Automation this month, the researchers trained their system to recognize different stages of an operation, such as biopsy, tissue removal, stapling, and wound cleansing.

But the system could be applied to any analytical question that doctors deem worthwhile. It could, for instance, be trained

Help make a ubiquitous model of decision processes more accurate

Markov decision processes are mathematical models used to determine the best courses of action when both current circumstances and future consequences are uncertain. They’ve had a huge range of applications — in natural-resource management, manufacturing, operations management, robot control, finance, epidemiology, scientific-experiment design, and tennis strategy, just to name a few.

But analyses involving Markov decision processes (MDPs) usually make some simplifying assumptions. In an MDP, a given decision doesn’t always yield a predictable result; it could yield a range of possible results. And each of those results has a different “value,” meaning the chance that it will lead, ultimately, to a desirable outcome.

Characterizing the value of given decision requires collection of empirical data, which can be prohibitively time consuming, so analysts usually just make educated guesses. That means, however, that the MDP analysis doesn’t guarantee the best decision in all cases.

In the Proceedings of the Conference on Neural Information Processing Systems, published last month, researchers from MIT and Duke University took a step toward putting MDP analysis on more secure footing. They show that, by adopting

The number of exposures necessary

Compressed sensing is an exciting new computational technique for extracting large amounts of information from a signal. In one high-profile demonstration, for instance, researchers at Rice University built a camera that could produce 2-D images using only a single light sensor rather than the millions of light sensors found in a commodity camera.

But using compressed sensing for image acquisition is inefficient: That “single-pixel camera” needed thousands of exposures to produce a reasonably clear image. Reporting their results in the journal IEEE Transactions on Computational Imaging, researchers from the MIT Media Lab now describe a new technique that makes image acquisition using compressed sensing 50 times as efficient. In the case of the single-pixel camera, it could get the number of exposures down from thousands to dozens.

One intriguing aspect of compressed-sensing imaging systems is that, unlike conventional cameras, they don’t require lenses. That could make them useful in harsh environments or in applications that use wavelengths of light outside the visible spectrum. Getting rid of the lens opens new prospects for the design of imaging systems.

“Formerly, imaging required a lens, and the lens would map pixels in space to sensors in an array, with everything precisely structured and engineered,” says Guy

The future of technology

When Alphabet executive chairman Eric Schmidt started programming in 1969 at the age of 14, there was no explicit title for what he was doing. “I was just a nerd,” he says.

But now computer science has fundamentally transformed fields like transportation, health care and education, and also provoked many new questions. What will artificial intelligence (AI) be like in 10 years? How will it impact tomorrow’s jobs? What’s next for autonomous cars?

These topics were all on the table on May 3, when the Computer Science and Artificial Intelligence Laboratory (CSAIL) hosted Schmidt for a conversation with CSAIL Director Daniela Rus at the Kirsch Auditorium in the Stata Center.

Schmidt discussed his early days as a computer science PhD at the University of California at Berkeley, where he looked up to MIT researchers like Michael Dertouzos. At Bell Labs he coded UNIX’s lexical-analysis program Lex before moving on to executive roles at Sun Microsystems, Novell, and finally Google, where he served as CEO from 2001 to 2011. In his current role as executive chairman of Google’s parent company, Schmidt focuses on Alphabet’s external matters, advising Google CEO Sundar Pichai and other senior leadership on business and policy.

Speaking with Rus on the topic

Communication networks from malicious hackers

Distributed planning, communication, and control algorithms for autonomous robots make up a major area of research in computer science. But in the literature on multirobot systems, security has gotten relatively short shrift.

In the latest issue of the journal Autonomous Robots, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory and their colleagues present a new technique for preventing malicious hackers from commandeering robot teams’ communication networks. The technique could provide an added layer of security in systems that encrypt communications, or an alternative in circumstances in which encryption is impractical.

“The robotics community has focused on making multirobot systems autonomous and increasingly more capable by developing the science of autonomy. In some sense we have not done enough about systems-level issues like cybersecurity and privacy,” says Daniela Rus, an Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT and senior author on the new paper.

“But when we deploy multirobot systems in real applications, we expose them to all the issues that current computer systems are exposed to,” she adds. “If you take over a computer system, you can make it release private data — and you can do a lot of other bad things. A cybersecurity attack

The clutter in online conversations

From Reddit to Quora, discussion forums can be equal parts informative and daunting. We’ve all fallen down rabbit holes of lengthy threads that are impossible to sift through. Comments can be redundant, off-topic or even inaccurate, but all that content is ultimately still there for us to try and untangle.

Sick of the clutter, a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has developed “Wikum,” a system that helps users construct concise, expandable summaries that make it easier to navigate unruly discussions.

“Right now, every forum member has to go through the same mental labor of squeezing out key points from long threads,” says MIT Professor David Karger, who was senior author on a new paper about Wikum. “If every reader could contribute that mental labor back into the discussion, it would save that time and energy for every future reader, making the conversation more useful for everyone.”

The team tested Wikum against a Google document with tracked changes that aimed to mimic the collaborative editing structure of a wiki. They found that Wikum users completed reading much faster and recalled discussion points more accurately, and that editors made edits 40 percent faster.

Karger wrote the new paper with PhD students

Process for positioning quantum bits in diamond

Quantum computers are experimental devices that offer large speedups on some computational problems. One promising approach to building them involves harnessing nanometer-scale atomic defects in diamond materials.

But practical, diamond-based quantum computing devices will require the ability to position those defects at precise locations in complex diamond structures, where the defects can function as qubits, the basic units of information in quantum computing. In today’s of Nature Communications, a team of researchers from MIT, Harvard University, and Sandia National Laboratories reports a new technique for creating targeted defects, which is simpler and more precise than its predecessors.

In experiments, the defects produced by the technique were, on average, within 50 nanometers of their ideal locations.

“The dream scenario in quantum information processing is to make an optical circuit to shuttle photonic qubits and then position a quantum memory wherever you need it,” says Dirk Englund, an associate professor of electrical engineering and computer science who led the MIT team. “We’re almost there with this. These emitters are almost perfect.”

The new paper has 15 co-authors. Seven are from MIT, including Englund and first author Tim Schröder, who was a postdoc in Englund’s lab when the work was done and is now an assistant professor

Creative approaches to connectivity

Daniel Zuo came to MIT with a plan: He wanted to study algorithms and one day to become a research professor.

The senior has more than accomplished the former goal, conducting innovative research on algorithms to reduce network congestion, in the Networks and Mobile Systems group at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). And, as he graduates this spring with a bachelor’s degree in computer science and electrical engineering and a master’s in engineering, he is well on his way to achieving the latter one.

But Zuo has also taken some productive detours from that roadmap, including minoring in creative writing and helping to launch MakeMIT, the nation’s largest “hardware hackathon.”

The next step in his journey will take him to Cambridge University, where he will continue his computer science research as a Marshall Scholar.

“The Marshall affords me the opportunity to keep exploring for a couple more years on an academic level, and to grow on a personal level, too,” Zuo says. While studying in the Advanced Computer Science program at the university’s Computer Laboratory, “I’ll be able to work with networks and systems to deepen my understanding and take more time to explore this field,” he says.

Algorithms to connect the

System allocates data center bandwidth more fairly

A webpage today is often the sum of many different components. A user’s home page on a social-networking site, for instance, might display the latest posts from the users’ friends; the associated images, links, and comments; notifications of pending messages and comments on the user’s own posts; a list of events; a list of topics currently driving online discussions; a list of games, some of which are flagged to indicate that it’s the user’s turn; and of course the all-important ads, which the site depends on for revenues.

With increasing frequency, each of those components is handled by a different program running on a different server in the website’s data center. That reduces processing time, but it exacerbates another problem: the equitable allocation of network bandwidth among programs.

Many websites aggregate all of a page’s components before shipping them to the user. So if just one program has been allocated too little bandwidth on the data center network, the rest of the page — and the user — could be stuck waiting for its component.

At the Usenix Symposium on Networked Systems Design and Implementation this week, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are presenting a new system for

Walking speed with wireless signals

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,”

Academic success despite an inauspicious start

When Armando Solar-Lezama was a third grader in Mexico City, his science class did a unit on electrical circuits. The students were divided into teams of three, and each team member had to bring in a light bulb, a battery, or a switch.

Solar-Lezama, whose father worked for an electronics company, volunteered to provide the switch. Using electrical components his father had brought home from work, Solar-Lezama built a “flip-flop” circuit and attached it to a touch-sensitive field effect transistor. When the circuit was off, touching the transistor turned it on, and when it was on, touching the transistor turned it off. “I was pretty proud of my circuit,” says Solar-Lezama, now an MIT professor of electrical engineering and computer science.

By the time he got to school, however, one of his soldered connections had come loose, and the circuit’s performance was erratic. “They failed the whole group,” Solar-Lezama says. “And everybody was like, ‘Why couldn’t you just go to the store and get a switch like normal people do?’”

The next year, in an introductory computer science class, Solar-Lezama was assigned to write a simple program that would send a few lines of text to a printer. Instead, he wrote a program

America opens headquarters steps from MIT campus

These are not your grandmother’s fibers and textiles. These are tomorrow’s functional fabrics — designed and prototyped in Cambridge, Massachusetts, and manufactured across a network of U.S. partners. This is the vision of the new headquarters for the Manufacturing USA institute called Advanced Functional Fabrics of America (AFFOA) that opened Monday at 12 Emily Street, steps away from the MIT campus.

AFFOA headquarters represents a significant MIT investment in advanced manufacturing innovation. This facility includes a Fabric Discovery Center that provides end-to-end prototyping from fiber design to system integration of new textile-based products, and will be used for education and workforce development in the Cambridge and greater Boston community. AFFOA headquarters also includes startup incubation space for companies spun out from MIT and other partners who are innovating advanced fabrics and fibers for applications ranging from apparel and consumer electronics to automotive and medical devices.

MIT was a founding member of the AFFOA team that partnered with the Department of Defense in April 2016 to launch this new institute as a public-private partnership through an independent nonprofit also founded by MIT. AFFOA’s chief executive officer is Yoel Fink. Prior to his current role, Fink led the AFFOA proposal last year as professor of materials