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It worked, of course. He headed to Cambridge and gravitated to MIT’s AI Lab in Technology Square, where he first worked on speech recognition and then switched to computer vision, then still in its infancy. After earning his doctorate, he worked simultaneously as a professor of computer science at Cornell and a researcher at Xerox PARC, flying between New York and the growing Silicon Valley, where he worked on computer vision for the digital transformation of copiers and scanners. “In academia you have more curiosity-driven research projects, where in the corporate world you have the opportunity to build things that people will actually use,” he says. “I’ve spent my career going back and forth between them.”
Along the way, Huttenlocher also gained administrative experience. He was a longtime board member and later president of the MacArthur Foundation, and also helped launch Cornell Tech, New York University’s graduate school of business, law and technology, serving as its first dean and provost. When Stephen Schwarzman, CEO of the investment firm Blackstone Group, gave MIT $350 million to establish a computer science school in 2018, he was eager to return to the Institute to lead it. “The fact that MIT made a bold commitment to become a broad leader in the AI-powered age—and permeated all of its schools—was exciting,” he says.
Schwarzman College took shape through working groups that included more than 100 MIT faculty members. By fall 2019, the plan was nailed down, with Huttenlocher as director and EECS head Ozdaglar named deputy dean for academies. “I never believed that everyone wanted to study computer science at MIT,” she says. “Students come with a lot of passion, and it’s our responsibility to educate these bilinguals to be fluent in their own discipline, but also able to use these advanced frontiers of computing.”
Ozdaglar has experience in using machine learning to optimize communication, transportation and control systems. She has recently become interested in applying machine learning algorithms to social media, examining how the choices people make when sharing content affects the information — and misinformation — that is recommended to them. This work builds on her many years of interdisciplinary collaboration in the social sciences, including with her husband, economics professor (and recent Nobel laureate) Daron Acemoglu. “I feel strongly that these old departments or disciplinary silos are no longer adequate to really address important issues in society,” she says. “College has allowed me to work much more broadly at MIT and share everything I’ve learned.”
Ozdaglar was the driving force behind faculty recruitment for the college, working with 18 departments to bring dozens of scientists to the forefront of computing. In a way, she says, it was a challenge to integrate new employees into existing disciplines. “We have to keep teaching what we’ve been teaching for tens or hundreds of years, so change is hard and slow,” she says. But she also noticed a palpable excitement about the new tools. The faculty has already brought in more than 30 new faculty members in four broad areas: climate and computing; human and natural intelligence; humanities and social sciences; and AI for scientific discovery. In any case, they are given an academic home in another department, as well as an appointment, and often laboratory space, within the college.
This commitment to interdisciplinary work is embedded in every aspect of the new headquarters. “Most of the buildings at MIT feel pretty monolithic,” Huttenlocher says as he leads the way through brightly lit hallways and large glass-walled common rooms that face Vassar Street. “We wanted to make this as open and accessible as possible.” While the Institute’s cutting-edge computing mostly takes place in a massive computer center in Holyoke, about 90 miles away in western Massachusetts, the building is dotted with labs and shared workspaces, all light and airy with glass and natural light wood. Along the corridor, open doors offer tantalizing glimpses of such things as a giant robot hanging from the ceiling amid a tangle of wires.
Laboratory and office space for faculty research groups working on related problems—which could be from, say, CSAIL and LIDS—are shared on the same floor to encourage interaction and collaboration. “It’s great because it builds connections between labs,” says Huttenlocher. “Even the conference room doesn’t belong in the lab or the college, so people actually have to work together to use it.” Another dedicated space is available for six months, upon application, for special cooperation projects. The first group to use it, last spring, focused on bringing computing to the climate challenge. To ensure that students also use the building, there is a 250-seat classroom and lecture hall, which now hosts the classic 6th course lectures (such as Introduction to Machine Learning) as well as new multidisciplinary lectures. A tall central lobby lined with comfortable booths and modular furniture is ready for learning.
For some of the new teachers, working at a college is a welcome change from previous academic experiences where they often felt caught between disciplines. “The intersection of climate sustainability and artificial intelligence was in its infancy when I started my PhD in 2015,” says Sherrie Wang, joint assistant professor of mechanical engineering and the Institute for Data, Systems and Society, who is principal investigator of the Earth Intelligence Lab. When she entered the job market in 2022, it was still not clear in which department she would be. Now part of Schwarzman’s climate cluster, she says her work uses machine learning to analyze satellite data, examining crop distribution and agricultural practices around the world. “It’s great to have a group of people who have similar philosophical motivations in applying these tools to real-world problems,” she says. “At the same time, we’re also pushing the tools forward.”
