The MIT Stephen A. Schwarzman College of Computing has awarded two inaugural chaired appointments to Dina Katabi and Aleksander Madry in the Department of Electrical Engineering and Computer Science (EECS).
“These distinguished endowed professorships recognize the extraordinary achievements of our faculty and future potential of their academic careers,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing and the Henry Ellis Warren Professor of Electrical Engineering and Computer Science. “I’m delighted to make these appointments and acknowledge Dina and Aleksander for their contributions to MIT, the college, and EECS, and their efforts to advance research and teaching in computer science, electrical engineering, artificial intelligence, and machine learning.”
Dina Katabi is the inaugural Thuan (1990) and Nicole Pham Professor. Katabi is being honored as an exceptional faculty member and for her commitment to mentoring students. Her work spans computer networks, wireless sensing, applied machine learning, and digital health. She is especially known for her work on a wireless system that can track human movement even through walls — a technology that has great potential for medical use.
Katabi is a member of the EECS faculty and is a principal investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL), as well as director of the Networks at MIT research group and co-director of the MIT Center for Wireless Networks and Mobile Computing. Among other honors, Katabi has received a MacArthur Fellowship, the Association for Computing Machinery (ACM) Prize in Computing, the ACM Grace Murray Hopper Award, two Test of Time Awards from the ACM’s Special Interest Group on Data Communications, a National Science Foundation CAREER Award, and a Sloan Research Fellowship. She is an ACM Fellow and was elected to the National Academy of Engineering.
Aleksander Madry has been named the inaugural Cadence Design Systems Professor. Established by Cadence Design Systems, the purpose of the position is to support outstanding faculty with research and teaching interests in the fields of artificial intelligence, machine learning, or data analytics. Madry’s research spans algorithmic graph theory, optimization, and machine learning. In particular, he has a strong interest in building on existing machine learning techniques to forge a decision-making toolkit that is reliable and well-understood enough to be safely and responsibly deployed in the real world.
Madry is a member of the EECS faculty, CSAIL, and the Theory of Computation Group, and is the director of MIT’s Center for Deployable Machine Learning, which brings together the broad expertise and focus needed to deploy machine learning systems.