PostDocs

Ming Yi is a postdoctoral research scientist in Data Science Institute at Columbia University. He received his Ph.D. degree in Electrical Engineering from Rensselaer Polytechnic Institute in 2022. He was a intern at the Argonne National Laboratory. He received a M.S. degree in Control Science and Engineering from the Harbin Institute of Technology in 2018 and a B.E. degree in Automation from Harbin Engineering University in 2016. His current research focuses on machine learning, energy storage, power system economics and resilience.

Ning Qi is a postdoctoral research scientist in Earth and Environmental Engineering at Columbia University. He received his Ph.D. degree in Electrical Engineering from Tsinghua University in 2023. Before joining Columbia, he was the postdoc at Digital Power System (DPS) lab at Department of Electrical Engineering, Tsinghua University. He was a visiting scholar at Technical University of Denmark in 2022. He received a B.E. degree in Electrical Engineering from Tianjin University in 2018. His current research focuses on data-driven modeling, optimization under uncertainty and market design for generic energy storage.

PhD Students

Ningkun (Nik) Zheng received B.S. degree from Zhejiang University, Zhejiang, China in 2018; M.S. degree from Johns Hopkins University, Baltimore, MD, USA, in 2019. Before joining Columbia, he was a research assistant at Carnegie Mellon Electricity Industry Center, Carnegie Mellon University, Pittsburgh, PA, USA. His research interests include power system economic and energy storage.

Liudong Chen received his B.S. and M.S. degrees in Electric Engineering from North China Electric Power University, Beijing, China. Before joining Columbia, he was a research assistant at State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China. His research interests include energy system economics and optimization and social behavioral modeling.

Zhiyuan Fan (joint with James Glynn) received his M.S. degree from Columbia University Mechanical Engineering and worked as research associate at the Center on Global Energy Policy. His research focuses on transitional energy infrastructure analysis using energy system modeling tools, especially energy infrastructure in supporting carbon-neutral economic development. He is also an active member of the Energy System Modeling Program at the Center on Global Energy Policy (CGEP), SIPA, Columbia University.

Saud Alghumayjan received his B.Sc. degree in Electrical Engineering from King Saud University in 2018 and his M.S. degree in Electrical Engineering from Columbia University in 2022. Before joining Columbia University he worked at the Center for Complex Engineering Systems at KACST and MIT as a Research Specialist where he tackled various problems related to power systems such as Electiricy Fraud Detection and Time-series Forecasting. Saud’s research interests are in the areas of machine and statistical learning, optimization, and computational modeling.

Elizabeth Cohn (joint with Upmanu Lall) received her B.S. degree in Electrical Engineering and Mathematics from Johns Hopkins University in 2020. Before joining the PhD program at Columbia University, she worked as a data scientist for Optum where she created AI/ML solutions to improve their health service offerings. Eliza’s research interests include renewable energy, the power grid, water systems, and methods to design equitable management strategies for the water-energy nexus in the face of climate change.

Visitors

Xueyuan Cui is a visiting student from The University of Hong Kong. He received his B.E. and M.S. degrees in Electrical Engineering from Zhejiang University in 2019 and 2022, respectively. He is now pursuing his Ph.D. degree at The University of Hong Kong. Before visiting Columbia, he was a visiting student at University of MONS, Belgium. His research interests include data-driven modeling and flexibility analysis of building energy systems.