Linda Jing

Linda Jing was an undergraduate in Materials Science and Engineering and minoring in Energy Studies with a concentration in Economics at MIT. Her research is focused on evaluating the materials constraints for energy storage.

Contact: weijing at mit dot edu

Dr. Ajinkya Kamat

Ajinkya Shrish Kamat is a postdoctoral associate at the Institute for Data, Systems, and Society (IDSS) at MIT. His research mainly centers on understanding how technology innovation capabilities are built, in industry and in higher education & research institutions, how these capabilities contribute to economic growth and development, and their policy implications. At IDSS, Ajinkya’s research focuses specifically on modeling energy technology systems to inform decarbonization efforts. Before joining MIT, Ajinkya was a postdoctoral research fellow jointly at the Belfer Center for Science and International Affairs of Harvard Kennedy School and at the Harvard’s Paulson School of Engineering and Applied Sciences. Ajinkya received his Ph.D. in Physics from the University of Virginia, M.Sc. in Physics from the Indian Institute of Technology-Bombay, India, and B.Sc. in Physics from the University of Mumbai, India.

contact: askamat at mit dot edu

Dr. Joel Jean

Joel Jean has a Ph.D. from the MIT Department of Electrical Engineering and Computer Science. His research with Vladimir Bulović in the MIT Organic and Nanostructured Electronics Laboratory (ONE Lab) focused on device physics and design of lightweight, flexible, and low-cost solar cells based on colloidal quantum dots and molecular semiconductors. Joel received his S.M. in Electrical Engineering from MIT and his B.S. in Electrical Engineering with distinction from Stanford University. He is a co-author of the MIT Future of Solar Energy Study and a recipient of the NSF Graduate Research Fellowship and the MIT Energy Fellowship. Joel has worked with the Trancik Lab on analyzing the potential impact of international emissions reduction pledges on solar PV and wind technology improvement and cost reductions.

Contact: jjean at mit dot edu

Frederik Boe Hüttel

Frederik Boe Hüttel is a visiting PhD student at the Institute for Data, Systems and Society (IDSS) at MIT. His PhD is done at the Machine Learning for Smart Mobility lab at the Technical University of Denmark (DTU) under the supervision of Francisco Camara Pereira. Frederik holds a BSc Eng. in Software Technology, focusing on the applications of machine learning models and an MSc Eng. in applied mathematical modelling, focusing on Machine Learning and Statistical Analysis. His main research interests include machine learning for demand modelling under uncertainty, which he applies to create intelligent and sustainable transportation systems. The main focus of Frederik’s PhD research is on the intersection between power systems and transportation modelling for electric vehicle infrastructure expansion.