I am a theoretical and computational scientist working at the intersection of machine learning and physical science. In one direction, I have worked on building foundations for deep learning and investigated core machine learning problems. In the other, I am interested in connections with and applications of machine learning to specific domains of physical science. A sample of topics from some of my past & ongoing work in this area includes:
See a recent Quanta magazine article for coverage on older work. I was trained as a theoretical quantum condensed matter physicist, and I received my Ph.D. in Physics from UC Berkeley in 2017. My graduate work is specifically in the field of quantum many-body theory and strongly correlated physics. I was fortunate to have Professor Ashvin Vishwanath as my thesis advisor. I worked on several areas as part of my doctoral research, including topological phases, many-body localization, and non-Fermi liquids. My dissertation proposed new classes of quantum behavior; new routes towards realizing exotic quantum phases; and new classes of mechanical behavior through topological mechanisms. I got started in theory as an undergraduate through research on tensor networks and entanglement in quantum systems with Professor Joel Moore at UC Berkeley, which was also the subject of my honors senior thesis. Contact: yasamanbahri@gmail.com Recent & Upcoming News
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