SIGEnergy Doctoral Dissertation Award 2022 winner

SIGEnergy establishes an annual Doctoral Dissertation Award to recognize an outstanding Ph.D. thesis in the field of energy systems and informatics.

As the inaugural year, we receive strong nominations and the award committee would like to thank the community for the great support to the endeavours. The competition has been fierce and the award committee is pleased to announce that the 2022 SIGEnergy Doctoral Dissertation Award winner goes to Priya Donti (PhD from CMU) for her thesis titled “Bridging Deep Learning and Electric Power Systems”.

Priya L. Donti received her Ph.D. in Computer Science and Public Policy from Carnegie Mellon University, co-advised by Zico Kolter and Inês Azevedo. She is the Co-founder and Executive Director of Climate Change AI, a global non-profit initiative to catalyze impactful work at the intersection of climate change and machine learning, which she is currently running through the Cornell Tech Runway Startup Postdoc Program. She will also join MIT EECS as an Assistant Professor in Fall 2023. Her research focuses on machine learning for forecasting, optimization, and control in high-renewables power grids. Specifically, her work explores methods to incorporate the physics and hard constraints associated with electric power systems into deep learning workflows. Priya is a recipient of the MIT Technology Review’s 2021 “35 Innovators Under 35” award, the Siebel Scholarship, the U.S. Department of Energy Computational Science Graduate Fellowship, and best paper awards at ICML (honorable mention), ACM e-Energy (runner-up), PECI, the Duke Energy Data Analytics Symposium, and the NeurIPS workshop on AI for Social Good.

The award committee is also pleased to present the 2022 SIGEnergy Doctoral Dissertation Award Honorable Mention: Tongxin Li (PhD from Caltech) for his thesis titled “Learning-Augmented Control and Decision-Making: Theory and Applications in Smart Grids”.

Tongxin Li received his Ph.D. in 2022 from Caltech where he was advised by Steven Low and Adam Wierman working on interdisciplinary topics in cyber-physical systems, machine learning, control, and optimization, and their applications in energy systems and sustainability. He has been invited to give talks at various international conferences and meetings such as the INFORMS Annual Meeting and INFORMS Applied Probability Conference. During his Ph.D., he interned as an applied scientist at AWS security in the summers of 2020 and 2021. He has participated in various projects on energy systems in collaboration with NREL, Pasadena Water and Power, and Caltech Facilities. He is a recipient of the 2021 Impact Grants from the Resnick Sustainability Institute. Tongxin Li is currently an assistant professor in the School of Data Science at The Chinese University of Hong Kong, Shenzhen, where he works on developing trustworthy artificial intelligence and machine learning techniques that improve the sustainability, robustness, scalability, privacy, and resilience of smart grids.

The award ceremony will be held on ACM e-Energy 2023, June 16-23, 2023, Orlando.