Top row, L to R: Ghobadi, Andreas, Sra. Bottom row, L to R: O'Brien, Reiskarimian, Agarwal.
School of Engineering
The School of Engineering is welcoming 11 new faculty members to its departments, institutes, labs, and centers.
With research and teaching activities ranging from the development of novel microscopy techniques to intelligent systems and mixed-autonomy mobility, they are poised to make significant contributions in new directions across the school and to a wide range of research efforts around the Institute. “I am pleased to welcome our outstanding new faculty,” says Anantha Chandrakasan, dean of the School of Engineering and Vannevar Bush Professor of Electrical Engineering and Computer Science. “Their contributions as educators, researchers, and collaborators will enhance the engineering community and strengthen our global impact.”
Among the new faculty members are six from EECS:
Pulkit Agrawal will join EECS as an assistant professor in July 2019. Agrawal received a bachelor's degree in electrical engineering from the Indian Institute of Technology, Kanpur, and was awarded the Director’s Gold Medal. He received a PhD in computer science from the University of California at Berkeley. A co-founder of SafelyYou, Inc., Agrawal researches topics spanning robotics, deep learning, computer vision, and computational neuroscience. His work has appeared multiple times in MIT Technology Review, Quanta, New Scientist, the New York Post, and other outlets. He is a recipient of the Signatures Fellow Award, a Fulbright science and technology award, the Goldman Sachs Global Leadership Award, OPJEMS, the Sridhar Memorial Prize, and IIT Kanpur’s academic excellence awards, among others. Agrawal also holds a “sangeet prabhakar” (the equivalent of bachelor’s degree in Indian classical music) and occasionally performs in music concerts.
Jacob Andreas will join EECS an assistant professor in July 2019. Andreas received a bachelor's degree from Columbia University and a master's in philosphy from the University of Cambridge, where he studied as a Churchill Scholar. He received a PhD from the University of California at Berkeley, where he was a member of the Berkeley Natural Language Processing Group and the Berkeley Artificial Intelligence Research Lab. His work is focused on using language as a scaffold for more efficient learning and as a probe for understanding model behavior. He has received the 2016 Annual Conference of the North American Chapter of the Association for Computational Linguistics Best Paper Award and the 2017 International Conference on Machine Learning Honorable Mention. He has been a National Science Foundation (NSF) Graduate Fellow, a Huawei-Berkeley AI Fellow, and a Facebook Fellow.
Manya Ghobadi joined EECS as an assistant professor in October. Previously, she was a researcher at the Microsoft Research Mobility and Networking group. Prior to Microsoft, she was a software engineer at Google. She received a PhD in computer science from the University of Toronto and a bachelor's degree in computer engineering from the Sharif University of Technology. A computer systems researcher with a networking focus, she has worked on a broad set of topics, including data-center networking, optical networks, transport protocols, network measurement, and hardware-software co-design. Many of the technologies she has helped develop are part of real-world systems at Microsoft and Google. She was recognized as an N2Women Rising Star in networking and communications in 2017. Her work has won the best dataset award, Google research excellent-paper award (twice), and the Association for Computing Machinery (ACM) Internet Measurement Conference best-paper award. nvolve quantum optics, nanophotonics, single molecule biophysics, and molecular diagnostics. In 2017, he received the Robert Dirks Molecular Programming Prize for his early career contributions to combining DNA nanotechnology and traditional semiconductor nanofabrication
Kevin O’Brien joined EECS as an assistant professor in July 2018. He earned a bachelor's degree in physics from Purdue University and a PhD in physics from the University of California at Berkeley. He joined the Quantum Nanoelectrics Lab (Siddiqi Group) at UC Berkeley as a postdoc to lead development of multiqubit quantum processors. His work has appeared in top journals, including Science, Nature Materials, and Nature Communications, among others. He has been an NSF Graduate Fellow. His research bridges nonlinear optics, metamaterials, and quantum engineering.
Negar Reiskarimian will join EECS as an assistant professor in July 2019. She received bachelor's and master's degrees in electrical engineering from Sharif University of Technology in Iran and is currently a PhD candidate in electrical engineering at Columbia University. She has published in top-tier IEEE IC-related journals and conferences, as well as broader-interest high-impact journals in the Nature family. Her research has been widely covered in the press and featured in IEEE Spectrum, Gizmodo, and EE Times, among others. She is the recipient of numerous awards and fellowships, including Forbes' “30 under 30,” a Paul Baran Young Scholar award, a Qualcomm Innovation Fellowship, and multiple IEEE awards and fellowships. She was a participant in the Rising Stars in EECS academic-careers workshop for women at Stanford University in 2017 and a speaker at the 2018 workshop at MIT.
Suvrit Sra joins EECS and the Institute for Data, Systems and Society (IDSS) as an assistant professor this month. He was a principal research scientist in the Laboratory for Information and Decision Systems (LIDS) at MIT. He receiveda PhD in computer science from the University of Texas at Austin in 2007. Before joining LIDS, he was a senior research scientist at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He has also held visiting faculty positions at UC Berkeley and Carnegie Mellon during 2013–14. His research bridges areas such as optimization, matrix theory, geometry, and probability with machine learning. More broadly, he is interested in data-driven questions within engineering, science, and health care. His work has won several awards at machine learning venues, as well as the 2011 SIAM Outstanding Paper Award. He founded the OPT Optimization for Machine Learning series of workshops at the Neural Information Processing Systems conference, which he has co-chaired since 2008; he has also edited a popular book with the same title (MIT Press, 2011).