SIGEnergy Doctoral Dissertation Award 2024 Winner

SIGEnergy establishes an annual Doctoral Dissertation Award to recognize an outstanding Ph.D. thesis in the field of energy systems and informatics. The key evaluation criteria are the depth, impact, and novelty of the thesis’ contributions.

For the 2024 cohort, the award committee has chosen the following award recipients:

SIGEnergy Doctoral Dissertation Award 2024 Winner: 

Xiang Pan, The Chinese University of Hong Kong, for thesis titled “Deep Neural Networks for Optimal Power Flow in Electric Power Systems: Design, Analysis, and Experiments”

Bio: Xiang Pan received his Ph.D. in Information Engineering from The Chinese University of Hong Kong in 2022. His research focuses on machine learning and its application in energy systems and multimedia signal processing, e.g., Neural Image Compression. Xiang is currently a researcher at Tencent Media Lab. He (as the core member) received the Winner Award of the CVPR 2018 Challenge on Learned Image Compression. During his Ph.D., he developed the DeepOPF as the first work in the literature that employs deep neural networks (DNN) to solve optimal power flow (OPF) problems directly by learning input-to-solution mapping. Once DNNs learn the mapping, they can be used to obtain quality solutions upon giving load inputs instantly without iteration, speeding up the computation time by 2~4 orders of magnitude compared to the state-of-the-art iterative OPF solvers. 

Xiang will receive the award at ACM BuildSys 2024, November 7-8, 2024, Hangzhou, China


SIGEnergy Doctoral Dissertation Award 2024 Honorable Mentions (in alphabetical order of last names):

Utkarsha Agwan, University of California Berkeley, for the thesis titled “Evaluating and Optimizing Distributed Energy Resources”

Bio: Utkarsha Agwan earned her doctorate from the Department of Electrical Engineering and Computer Sciences at UC Berkeley. Her research focused on distributed energy resources, specifically batteries, electric vehicles and flexible loads, and how they can participate in the larger power grid. The overarching theme of her work is climate change mitigation. She also works as a consultant for companies in the smart energy space, with projects on distributed generation, storage, and local energy markets. Currently, Utkarsha works as a Senior Data Scientist at C3 AI, and previously obtained her undergraduate degree in Electrical Engineering from IIT Delhi.

Utkarsha is likely to receive the award at ACM BuildSys 2024, November 7-8, 2024, Hangzhou, China


John Wamburu, University of Massachusetts Amherst, for the thesis titled “Data-driven Modeling and Analytics for Greening the Energy Ecosystem”

Bio: John Wamburu received his Ph.D. in 2023 from the University of Massachusetts

Amherst where he worked on interdisciplinary topics cutting across cyber-physical systems and green energy. Specifically, his work applied techniques from machine learning, statistical time-series analysis and optimization in energy analytics and greening the energy ecosystem. During his Ph.D., he interned at the IBM T.J. Watson Research Center and LinkedIn. He is also an avid inventor with more than 10 patents under his name. John Wamburu is currently a Research Scientist at IBM Research Africa in Nairobi, Kenya, where he works on trustworthy AI and anomalous pattern discovery.

John will receive the award at ACM e-Energy 2024, June 4-7, 2024, Singapore.