Harder, better, faster, stronger

Imagine if you and a group of students were tasked with designing, building, testing, and driving a Formula-style electric race car from the ground up. Every year.

For students who are members of MIT Motorsports — a.k.a. the MIT Formula SAE (FSAE) team, originally founded in 2001 — that task determines how they spend their free time, on weekends, evenings, and often, January Independent Activities Period as well as summer.

On a recent Saturday in the Edgerton Center’s Area 51 Student Shop (Room N51), about two dozen students on the FSAE team were sitting at large work tables, huddled over their laptops, designing components for their 2017 vehicle using the Solidworks design software. Friendly banter, shared jokes, and periods of serious focus characterized the day. One student, senior Brian Wanek, sat wearing a helmet inside a prototype of what would be the driver’s seat, while sophomore Wasay Anwer measured the frame.

The task for this year — borrowing from a Daft Punk song — is building a harder, better, faster, stronger car for the June 2017 Collegiate Design Series hosted by the Society of Automotive Engineers in Lincoln, Nebraska.

Last year’s performance was nothing to shrug at. MIT's team passed all inspections, placed fourth in vehicle cost (spending the least amount of money to construct the car), placed fourth overall in design, and sixth overall in a field of 21 teams from around the globe.

“Our previous car was an evolutionary step in our team’s history,” says team captain and MIT junior Luis Alberto Mora, who joined FSAE as a freshman. “We kept the working components the same and made minor improvements on previous designs. This year’s car is a revolutionary step; brand new electric powertrain and batteries, new tire size, giving us the freedom to make no compromises in performance.”

The team operates on a tight budget, just over $100,000, and they actively raise funds from sponsors inside and outside of MIT. The Edgerton Center, the Department of Mechanical Engineering, Ford Motor Company, and General Motors provide the bulk of funding necessary to keep the team running year after year.

More than 1,000 parts go into the construction of their car, most of which is fabricated in the shop using a mix of manual and computer numeric control (CNC) machines, rapid prototyping machines, and water jet cutters. The team typically purchases all the raw materials needed to build their new car, as well as high-cost items such as battery cells, electric motors, and motor controllers. 

This year the team is designing their own battery pack based off of high-discharge lithium-ion cy­lindrical cells. “Our previous battery pack [used on last year’s car] was purchased by a company that later went out of business and needed lots of repairs. We gained a lot of knowledge from having to fix it,” says Elliot Owen, a junior in mechanical engineering and battery lead for MIT FSAE. “This year’s battery pack will have a different chemistry in a different format. Previously we had big floppy sheets, now we have little canisters, similar to what is used in Tesla. We can make a 25 percent weight reduction, we have more energy, and it’s safer,” Owen says.

The lighter car weighs in at 215 kilograms without a driver, 30 kg lighter than last year’s vehicle. The new car will have a chassis and suspension of a hybrid design: a primary steel tube structure with stressed carbon fiber panels.

Last year’s car also serves a purpose for this year’s build. “We can try out new software on the old car, we can debug it, and by the time the new car is built, the software, the mechanical parts, are already worked out,” Mora says.

To sustain a team that, without fail, loses a number of valuable team members each year to graduation is no small task — and recruiting new members is essential. Tianye Chen, a junior in electrical engineering and computer science who is the low voltage electrical systems lead, says: “We try to give new members meaningful things to do, teach them how to use the tools, and give them projects to keep them engaged.”

Patrick McAtamney, technical instructor and master machinist in Area 51, works closely with the FSAE team and sees multiple benefits being on an Edgerton Center team. “One thing that students get are social skills, how to work with other team members on sub teams, a mechanical engineering student will work with an aero-astro student to solve engineering problems together.”

“FSAE provides one of the most real-world engineering experiences offered on campus,” says assistant professor of mechanical engineering Amos Winter, the team’s faculty advisor who meets with them regularly to go over design specifications. “As an educator, it makes me very happy to see the students absorb, synthesize, and apply the theory we teach in classes into practical engineering solutions.”

While the June competition is still a ways off, for the FSAE students it will mark the culmination of a year-long project of long hours, hard work, and fun — a noteworthy accomplishment for all.

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Creating videos of the future

Living in a dynamic physical world, it’s easy to forget how effortlessly we understand our surroundings. With minimal thought, we can figure out how scenes change and objects interact.

But what’s second nature for us is still a huge problem for machines. With the limitless number of ways that objects can move, teaching computers to predict future actions can be difficult.

Recently, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have moved a step closer, developing a deep-learning algorithm that, given a still image from a scene, can create a brief video that simulates the future of that scene.

Trained on 2 million unlabeled videos that include a year’s worth of footage, the algorithm generated videos that human subjects deemed to be realistic 20 percent more often than a baseline model.

The team says that future versions could be used for everything from improved security tactics and safer self-driving cars. According to CSAIL PhD student and first author Carl Vondrick, the algorithm can also help machines recognize people’s activities without expensive human annotations.

“These videos show us what computers think can happen in a scene,” says Vondrick. “If you can predict the future, you must have understood something about the present.”

Vondrick wrote the paper with MIT professor Antonio Torralba and Hamed Pirsiavash, a former CSAIL postdoc who is now a professor at the University of Maryland Baltimore County (UMBC). The work will be presented at next week’s Neural Information Processing Systems (NIPS) conference in Barcelona.

How it works

Multiple researchers have tackled similar topics in computer vision, including MIT Professor Bill Freeman, whose new work on “visual dynamics” also creates future frames in a scene. But where his model focuses on extrapolating videos into the future, Torralba’s model can also generate completely new videos that haven’t been seen before.

Previous systems build up scenes frame by frame, which creates a large margin for error. In contrast, this work focuses on processing the entire scene at once, with the algorithm generating as many as 32 frames from scratch per second.

“Building up a scene frame-by-frame is like a big game of ‘Telephone,’ which means that the message falls apart by the time you go around the whole room,” says Vondrick. “By instead trying to predict all frames simultaneously, it’s as if you’re talking to everyone in the room at once.”

Of course, there’s a trade-off to generating all frames simultaneously: While it becomes more accurate, the computer model also becomes more complex for longer videos. Nevertheless, this complexity may be worth it for sharper predictions.

To create multiple frames, researchers taught the model to generate the foreground separate from the background, and to then place the objects in the scene to let the model learn which objects move and which objects don’t.

The team used a deep-learning method called “adversarial learning” that involves training two competing neural networks. One network generates video, and the other discriminates between the real and generated videos. Over time, the generator learns to fool the discriminator.

From that, the model can create videos resembling scenes from beaches, train stations, hospitals, and golf courses.  For example, the beach model produces beaches with crashing waves, and the golf model has people walking on grass.

Testing the scene

The team compared the videos against a baseline of generated videos and asked subjects which they thought were more realistic. From over 13,000 opinions of 150 users, subjects chose the generative model videos 20 percent more often than the baseline.
 
Vondrick stresses that the model still lacks some fairly simple common-sense principles. For example, it often doesn’t understand that objects are still there when they move, like when a train passes through a scene. The model also tends to make humans and objects look much larger in size than reality.

Another limitation is that the generated videos are just one and a half seconds long, which the team hopes to be able to increase in future work. The challenge is that this requires tracking longer dependencies to ensure that the scene still makes sense over longer time periods. One way to do this would be to add human supervision.

“It’s difficult to aggregate accurate information across long time periods in videos,” says Vondrick. “If the video has both cooking and eating activities, you have to be able to link those two together to make sense of the scene.”

These types of models aren’t limited to predicting the future. Generative videos can be used for adding animation to still images, like the animated newspaper from the Harry Potter books. They could also help detect anomalies in security footage and compress data for storing and sending longer videos.

“In the future, this will let us scale up vision systems to recognize objects and scenes without any supervision, simply by training them on video,” says Vondrick.

This work was supported by the National Science Foundation, the START program at UMBC, and a Google PhD fellowship.

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How online tools and open innovation can support implementation of Paris Agreement goals

An MIT research initiative is harnessing the power of crowds and online collaborative tools in support of fulfilling global Paris Agreement climate goals.

MIT’s Climate CoLab, founded and directed by Professor Thomas Malone of the MIT Center for Collective Intelligence, presented its work and innovative approach in a series of events earlier this month at the United Nations Framework Convention on Climate Change (UNFCCC) Conference of the Parties in Marrakech, Morocco (COP22). Climate CoLab’s team was on the ground in Marrakech to strengthen and build new collaborations with the international community in support of the 2015 Paris international climate agreement, and to showcase the role crowds and online collaborative tools can play in supporting implementation of the Paris Agreement goals. Of the project, Malone said: “It’s now possible to harness the collective intelligence of thousands of people, all over the world, at a scale, and with a degree of collaboration, that was never possible before in human history."

Amid notable milestones in international climate cooperation this fall — including the early legal entry into force of the Paris Agreement, a recent international accord on reducing global hydrofluorocarbons (HFCs), and another on reducing emissions from the aviation sector, COP22 was still awash with reminders of the stark scientific realities that further near-term action is needed to combat the most dangerous impacts of climate change. Among them, a new United Nations' Environmental Program 2016 Emissions Gap Report, released immediately prior to COP22, projected that 25 percent greater global emissions cuts are needed prior to 2030. UN Secretary-General Ban Ki-moon recently urged the global community, “We are still in a race against time. We need to transition to a low-emissions and climate-resilient future.”

Climate CoLab is pioneering a crowd-based methodology to help meet this challenge. The project was highlighted during several events at COP22, including two official UN side events, and a featured interview with the UNFCCC Climate Change Studio. “What if we could harness all of the ingenuity and intelligence of everybody that’s [at COP22], and also everybody that couldn’t be here today, to continuously work together on climate change solutions? What could be possible?” said Laur Hesse Fisher, Climate CoLab project manager, during the interview. “New digital collaboration tools enable that,” she continued.

On Monday, Nov. 14, Climate CoLab co-hosted an official side event with collaborator Climate Interactive and the Abibimman Foundation, entitled “Meeting the Paris Goals through Decision-Maker Tools and Climate Education.” Panelist Andrew Jones, Climate Interactive’s co-director, started the session with the premise that we need large-scale engagement in order to adequately address this challenge: “We don’t need 10,000 experts, we need 1 billion amateurs doing all they can, effectively, to make change.”

The role of non-state actors and open transparent stakeholder engagement processes were featured throughout COP22. On Nov. 15, Hesse Fisher joined a panel of collaborators from various international organizations, including Climate Policy Institute, Climate-KIC, the Global Environmental Facility, ICLEI, and many others, organized by the Cities Climate Finance Leadership Alliance. Addressing an audience of government officials, academics, non-profit advocates, and others, the panelists discussed the role of innovation platforms and tools in helping finance climate action.

Additionally, building on last year’s launch of a partnership with the UN Secretary-General’s Climate Resilience Initiative: Absorb, Anticipate, Reshape (A2R), Climate CoLab was featured in an A2R brochure distributed at A2R Initiative COP22 events, for its new contest on “Anticipating Climate Hazards,” which seeks proposals on early warning systems and climate preparedness responses. Of the collaboration, Malone said, “To contend with the most pressing impacts of climate change, it is clear that now more than ever before, we need ideas and contributions of as many people as possible to address climate change.”

As focus turns to accelerating countries’ implementation of their emissions reductions targets and adaptation strategies put forward under the Paris Agreement — also known as “nationally-determined contributions” or “NDCs” — Climate CoLab is exploring how this online collaborative approach of stakeholder engagement and expert-validated climate planning including assessment could prove valuable to countries. Building on themes of open engagement and enhancing transparency, Malone remarked, “We believe it’s possible to open up the national and international climate planning processes to anyone around the world who wants to participate.” As Fisher said, this approach provides “new ways that the world can work together.”

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Climate models may be overestimating the cooling effect of wildfire aerosols

Whether intentionally set to consume agricultural waste or naturally ignited in forests or peatlands, open-burning fires impact the global climate system in two ways which, to some extent, cancel each other out. On one hand, they generate a significant fraction of the world’s carbon dioxide emissions, which drive up the average global surface temperature. On the other hand, they produce atmospheric aerosols, organic carbon, black carbon, and sulfate-bearing particulates that can lower that temperature either directly, by reflecting sunlight skyward, or indirectly, by increasing the reflectivity of clouds. Because wildfire aerosols play a key role in determining the future of the planet’s temperature and precipitation patterns, it’s crucial that today’s climate models — upon which energy and climate policymaking depend — accurately represent their impact on the climate system.

But a new study in Atmospheric Chemistry and Physics by researchers at the MIT Joint Program on the Science and Policy of Global Change shows that at least one widely-used climate model is overestimating the cooling effect of these aerosol emissions by as much as 23 percent.

“This overestimation could lead to errors in projections of surface temperature and rainfall, both globally and regionally,“ says Chien Wang, a senior research scientist at MIT’s Department of Earth, Atmospheric and Planetary Sciences and the Joint Program, who co-authored the paper with two members of his group: lead author and research scientist Benjamin S. Grandey and postdoc Hsiang-He Lee of the Center for Environmental Sensing and Modeling at the Singapore-MIT Alliance for Research and Technology. “We hope our findings will reduce such errors in climate modeling.”

To make long-term global projections, most climate models represent atmospheric wildfire aerosol emissions by using monthly measures of emissions at different locations around the globe, and then averaging those emissions over multiple years — before estimating their effect on solar radiation at each location over the multi-year period. Questioning the accuracy of this conventional approach, the researchers proposed a revised representation of wildfire aerosol emissions in which the radiative effect associated with each monthly measure of emissions is first calculated, before averaging over the multi-year period. The revised approach would account for year-to-year variability in the aerosols’ radiative effect, which is missing in the conventional representation.

Using a global aerosol-climate model — the Community Earth System Model (CESM) — and the Global Fire Emissions Database (GFED4.0s), the researchers compared both modeling approaches over a 10-year period. The comparison showed that wildfire emissions are responsible for a global mean net radiative effect of about -1.26 watts per square meter for the conventional approach, and about -1.02 watts per square meter for the revised approach. The conventional climate modeling approach systematically overestimated the strength of the net radiative effect of wildfire aerosols — by 23 percent globally and by higher levels (58 percent over Australia and New Zealand; 43 percent over Boreal Asia, where wildfires are commonplace) regionally.

The researchers attribute this systematic overestimation to the non-linear influence of the aerosols on clouds, due largely to interactions between organic carbon aerosols and clouds. Organic carbon aerosols initially boost the reflectivity (and thus cooling effect) of clouds, but as concentrations increase over a particular geographic location, the rate of increase in cloud reflectivity (and cooling effect) slows down considerably. By incorrectly assuming that the indirect cooling effect of aerosol emissions increases linearly with their concentration, conventional approaches overestimate that effect in climate models.

Representing the year-to-year variability in the cooling effect of wildfire aerosols in climate models could improve our understanding of the climate system and the overall accuracy of global and regional climate projections.

“Hopefully what we’ve found here will be taken into account in future climate modeling studies, which could help improve decision-making regarding climate mitigation and adaptation,” says Grandey.

The research team recommends further research to test the robustness of their method by using different climate models and wildfire emissions data sets, improve the scientific understanding of the mechanisms behind the results, and explore in greater depth the impact of year-to-year variation in aerosol emissions on different aspects of climate change.

The research was funded by the Singapore National Research Foundation through the Singapore-MIT Alliance for Research and Technology's Center for Environmental Sensing and Modeling, as well as by grants from the National Science Foundation, the Department of Energy, and the Environmental Protection Agency.

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Professor Hung Cheng pledges $1 million for a new MIT scholarship

MIT professor of applied mathematics Hung Cheng has pledged $1 million to establish a new scholarship for MIT students. The Hung and Jill Cheng Scholarship Fund will fully support undergraduates beginning this academic year.

Cheng was inspired to establish the scholarship through writing his novel, "Nanjing Never Cries" (MIT Press, 2016), which follows four people as they survive the 1937 Nanjing massacre and cope with its aftermath during the Sino-Japanese War. The scholarship will give first preference to students from Nanjing, China, and then to students from China and to students of Chinese descent.

MIT plays a special role in the lives of the characters of Cheng’s novel. John Winthrop, an American, and Calvin Ren, a Nanjing native, meet at MIT, where they build a close friendship as they study, physics, aeronautical engineering, and mechanical engineering. When Winthrop accepts Ren’s invitation to work with him on designing and building airplanes in China on the eve of the Sino-Japanese War, they discover that their strong bond and strong education in science and technology have given them the means to make a significant practical contribution to the Chinese war effort.

Cheng believes that MIT is uniquely qualified to prepare students to do the kind of world-changing work accomplished by the characters in his novel, and hopes that his new scholarship will enable more students access the valuable education and supportive community that MIT offers.

“You have a lot of very smart and hardworking people here, talking to each other and being friends, and they all benefit from each other,” Cheng says. “To be nurtured by this environment helps us grow and to become a more useful person. MIT students can do a lot of good — to help wipe out poverty, develop energy, and to help implement medical sciences. If you learn a science or technology background very well from MIT, you can turn it into a very valuable experience and do something useful for humanity.”

Although Cheng’s book is fictional, its characters and events of the book draw in part on Cheng’s own experience growing up in China and as a professor. Born in China in 1937, just a few months after the beginning of the Sino-Japanese War, Cheng moved to Taiwan as a teenager and then moved to the United States to pursue undergraduate studies at Caltech. After earning his BS in 1959, he stayed at Caltech, earning his PhD in in only two years. After postdoctoral appointments at Caltech, Princeton University, and Harvard University, he came to MIT as an assistant professor in 1965 and rose to the rank of full professor four years later. Since then, he has made significant contributions to gauge-field theory, working with Harvard’s T. T. Wu to formulate an unexpected prediction that the cross-section of colliding protons increases with energy, which The New York Times announced was experimentally confirmed at CERN in 1973. He has also worked on problems in unified field theory related to scale invariance and general relativity.

“I am delighted that my friends Hung Cheng and Jill Tsui have made this gift to MIT,” said Michael Sipser, dean of the MIT School of Science. “Professor Cheng has been my colleague at MIT for many years, and we both know that to solve our most difficult and important problems, MIT needs motivated and creative students. Endowed scholarships make it possible for all brilliant students — even those with limited financial resources — to join our community.”

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MIT Skoltech Seed Fund issues call for proposals

The MIT Skoltech Seed Fund Program is calling for proposals, now through Dec. 23, from MIT faculty and researchers with principal investigator status for innovative projects that have the potential to benefit the development of the MIT Skoltech Program or the mission of the Skolkovo Foundation. The program strongly encourages proposals that involve collaborative research with Skoltech or other Russian academic and research institutions.  

Interested researchers are encouraged to submit proposals in the following three main categories:

• research projects in science and engineering (biomedicine, energy, information technology, data science and computational modeling, product design and manufacturing, and space);

• research projects in the areas of policy, economics, humanities, arts and social sciences (especially innovation and entrepreneurship, international collaborative programs, technology and policy, and general Russian studies, including Russian history, Russian art and Russian economy); and

• non-research projects to promote engagement and collaboration on topics and activities that may impact Russia, Skoltech, or other Russian institutions — such as course development, course teaching, student exchange, event organization (e.g., a hackathon or other application-type activity), etc.

The MIT Skoltech Seed Fund will award grants in amounts up to $75,000, for one year.

The application deadline is Friday Dec. 23. For more information and to apply, visit the Skoltech Seed Fund page. 

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MIT Reads hosts author Janet Mock

MIT Reads, an Institute-wide reading and discussion program, welcomed author, editor, and media professional Janet Mock to a full Kirsch Auditorium Nov. 15 for a conversation about her memoir, "Redefining Realness."

Seated in easy chairs on the stage just one week after the presidential election, Mock and moderator / MIT junior Syn Odu started a timely discussion with Odu’s own questions and then took more from the audience.

As a mixed-race trans woman of color, Mock spoke openly about the fears that the 2016 election results have provoked, in her words, in “brown folk, undocumented folk, black folk, queer folk, trans folk, and disabled people [who] are now having to fight even more to say that we deserve to be here.”

But Mock’s message was not one of fear or defeat. In the election, Mock said she supported Hillary Clinton, but now, “We have a better option, and it’s us. We have to do the work now.” She urged those gathered to deepen their communities, get involved in grassroots organizations that support marginalized populations, and seek out safe places where they can process and heal.

The timing of this author event could not have been more perfect, said PhD student Danielle Olson. “I am a woman of color at MIT and a strong ally of the LBGTQ+ community,” she said. “Last Wednesday I came to campus feeling hyper visible as a black woman on campus — not because MIT isn’t diverse, but [because of] this past election cycle.” Olson, an undergraduate alumna of MIT who returned as a graduate student in electrical engineering and computer science, says MIT Reads is one of several new opportunities she’s found across campus to support students and give them safe spaces to connect with one another. The program’s inaugural reading selection was also a pleasant surprise. “I am so happy we chose this author,” she said.

“We had a wonderful cross section of the MIT community attend,” said Nina Davis-Millis, who coordinates MIT Reads as part of her role as the director of Community Support and Staff Development at MIT Libraries. “It was a wonderful example of [Director Chris Bourg’s] vision of the libraries being a place on campus where people can have difficult discussions.”

During the question-and-answer portion of the evening, the audience wanted to know how Mock worked through the difficulties of her young life growing up poor and transgender. As an adult, Mock said, she has relied on community and self-care: “Finding spaces in which I can show up and not have to perform or be some kind of leader or figurehead. Where I just show up and be empty and not have to give anyone anything. That helps me process. Writing has always helped me process. Reading has always helped me process.”

The conversational format and intimacy of the discussion struck Dan Calacci, a first-year master’s student in media arts and sciences. “It was unique because it was really just two people who cared quite a bit about intersectional issues having a conversation — and a very personal conversation at that,” he said. “As a white person somewhere between queer and cis, it was super nice to be able to drop in on a conversation like that and hear from people who have thought deeply about these issues.”

The timing was necessary given the events of the prior week, according to Julio Oyola, assistant director of LBGTQ Services at MIT’s Rainbow Lounge. Mock met with a small group of invited students before the public event. Oyola said it was an opportunity to “express their gratitude for her serving as a role model for them as trans folk and queer students of color. It was moving and remarkable especially in light of how some folks are feeling.”

The conversation with Mock was co-sponsored by the Division of Student Life, the Office of the Dean for Graduate Education, the Sloan School Student Life Office, and the Program in Media Arts and Sciences. The author event is one of several community events facilitated by MIT Reads this fall, including smaller group discussions scheduled to accommodate not only students and faculty but also staff and other MIT affiliates.  

MIT Reads’ launch comes at a time when community dialogue is more important than ever. Its enthusiastic response across MIT has heartened Davis-Millis: “The thing that really made my heart sing was the idea of the MIT community getting excited about a book and coming together around the act of reading.”

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