Jack Hare joined the Department of Nuclear Science and Engineering as an assistant professor in January. He received his BA (2010) and his MSci (2011) in Natural Sciences from the University of Cambridge, his MA in Plasma Physics from Princeton University in 2013, and his PhD in Plasma Physics from Imperial College, London in 2017. After his PhD, he held postdoctoral appointments at Imperial College London, where he has researched magnetized turbulence in high-energy-density plasmas, and at the Max-Planck Institute for Plasma Physics, where he worked on the design of diagnostics for the ITER fusion reactor project. At MIT, his research will focus on fundamental plasma processes in magnetized high energy density plasmas, such as magnetic reconnection and magneto-hydrodynamic turbulence. These plasmas are created using intense pulses of electrical current generated by the new PUFFIN pulsed-power facility, hosted on campus at the Plasma Science and Fusion Center.

Dylan Hadfield-Menell will join the Department of Electrical Engineering and Computer Science as an Assistant Professor in July. Hadfield-Menell received his PhD in Computer Science from UC-Berkeley, and his MS and BS (both in Computer Science and Electrical Engineering) from MIT. His research focuses on the value alignment problem in artificial intelligence, and aims to help create algorithms that pursue the intended goals of their users. He is also interested in work that bridges the gap between AI theory and practical robotics, and the problem of integrated task and motion planning. Hadfield-Menell is an NSF Graduate Research Fellowship Recipient and a Berkeley Fellow, with multiple conference papers published in the AAAI/ACM Conference on AI, Ethics, and Society and the ACM/IEEE International Conference on Human-Robot Interaction, among others. He was the technical lead on The Future Starts Here Exhibit for the Victoria and Albert Museum, and has interned at Facebook and Microsoft.

Marzyeh Ghassemi will join the Institute for Medical Engineering and Science and the Department of Electrical Engineering and Computer Science as an Assistant Professor in July. She received her PhD in Computer Science from MIT; her MS in Biomedical Engineering from Oxford University; and two BS degrees, in Electrical Engineering and Computer Science, from New Mexico State University. Her research focuses on creating and applying machine learning to human health improvement. Ghassemi’s work has been published in topconferences and journals including NeurIPS, FaCCT, The Lancet Digital Health, JAMA, the AMA Journal of Ethics, and Nature Medicine, and featured in popular press such as MIT News, NVIDIA, and the Huffington Post. A British Marshall Scholar and American Goldwater Scholarwho has completed graduate fellowships at organizations including Xerox and the NIH, Ghassemi has been named one of MIT Tech Review’s 35 Innovators Under 35. Ghassemi organized MIT’s first Hacking Discrimination event and was awarded MIT’s 2018 Seth J. Teller Award for Excellence, Inclusion and Diversity. She also is on the Senior Advisory Council of Women in Machine Learning (WiML) and founded the ACM Conference on Health, Inference and Learning (ACM CHIL).

Rodrigo Freitas joined the Department of Materials Science and Engineering (DMSE) in January as the AMAX Assistant Professor. He received his BSc and MSc degrees in Physics from the University of Campinas in Brazil, and MSc and PhD degrees in Materials Science and Engineering from the University of California Berkeley, followed by postdoctoral work at Stanford University. During his PhD, he was also a Livermore Graduate Scholar in the Materials Science Division of the Lawrence Livermore National Laboratory. He uses a combination of theoretical, computational, and data-driven approaches to study the mechanisms of microstructure evolution in materials. This research area is critical to understand and control materials kinetics at the microstructure level, and it has broad potential impact and application, which will lead to collaborations across DMSE and in the Schwarzman College of Computing.

Navid Azizan will join the MIT faculty with dual appointments in the Department of Mechanical Engineering and the Institute for Data, Systems, and Society (IDSS) as an assistant professor in September. He is currently a postdoctoral scholar in the Autonomous Systems Laboratory at Stanford University. He received his PhD in Computing and Mathematical Sciences (CMS) from the California Institute of Technology (Caltech) in 2020, his MSc from the University of Southern California in 2015, and his BSc from Sharif University of Technology in 2013. Additionally, he was a research intern at Google DeepMind in 2019. Azizan’s research interests broadly lie in machine learning, control theory, mathematical optimization, and network science. He has made fundamental contributions to various aspects of intelligent systems, including the design and analysis of optimization algorithms for nonconvex and networked problems with applications to the smart grid, distributed computation, epidemics, and autonomy. Azizan’s work has been recognized by several awards including the 2020 Information Theory and Applications (ITA) Graduation-Day Gold Award. He was named an Amazon Fellow in Artificial Intelligence in 2017 and a PIMCO Fellow in Data Science in 2018. His research on electricity markets received the ACM GREENMETRICS Best Student Paper Award in 2016. He was also the first-place winner and a gold medalist at the 2008 National Physics Olympiad in Iran. He co-organizes the popular “Control meets Learning” virtual seminar series.