Our work on mixed-signal computing for power electronics has been accepted for publication in the IEEE Transactions on Power Electronics and is available as a preprint on TechRxiv. We demonstrate a hardware prototype of a neuromorphic-inspired computing platform for solving complex optimal control problems in real-time.
Presented our work at APEC 2021 on a mixed-signal computing platform for solving online optimization problems for power electronics systems in a fast and energy-efficient manner. See the conference paper for more details.
Delivered a lecture titled ‘The Power Electronics-Enabled Smart Grid’ for the Stanford Smart Grid Seminar. A recording of the event is available here.
Our latest work has been published in the IEEE Transactions on Power Electronics and is available on IEEE Xplore. We show how minimum distortion point tracking can significantly improve the power quality and stability of large-scale, distributed solar inverter systems.
Presented an overview poster of my latest research at an NSF-sponsored workshop on power systems and machine learning in Alexandria, VA
Our work on minimum distortion point tracking is available on IEEE Xplore. This work presents a new decentralized control strategy for networks of dc-dc converters that can reduce harmonic noise by more than two orders of magnitude for some applications.
Elected Vice Chair of the IEEE PELS San Francisco Bay Area Chapter
Attended NSF Workshop on Power Electronics-enabled Operation of Power Systems in Chicago
Invited participant at the Fort Collins 2019 Symposium on Microgrids
Received the 2019 EERE Postdoctoral Research Award from the Department of Energy
Participant in the Workshop on Grid-Forming Inverters for Low-Inertia Power Systems in Seattle
Seminar presentation at the IEEE PELS San Francisco Bay Area Chapter meeting
Invited seminar at MIT EECS
Invited seminar at Lawrence Berkeley National Laboratory