About
Steven H. Low is the Frank J. Gilloon Professor of Computing and Mathematical Sciences and Electrical Engineering at the California Institute of Technology (Caltech). He holds a joint appointment in the Division of Engineering and Applied Science, contributing to interdisciplinary research at the intersection of power systems, control theory, and machine learning. His work focuses on optimizing electrical grids, smart infrastructure, and networked systems.
Key research interests include optimal power flow (OPF) solutions, stability analysis of power systems, reinforcement learning applications in energy networks, and adaptive charging networks for electric vehicles. He has pioneered methodologies for decentralized control, contingency planning, and data-driven approaches to enhance grid resilience and efficiency.
His recent publications explore digital twins for distribution grids, three-phase network analysis, and uncertainty-aware capacity expansion strategies. He is a member of the RSI Education Committee and leads initiatives like the Adaptive Charging Network Research Portal. His contributions bridge theoretical advancements with real-world implementations in energy systems and smart infrastructure.
Low’s research emphasizes practical scalability, often addressing challenges such as real-time voltage control, line failure mitigation, and privacy-preserving data sharing in smart grids. His work integrates mathematical rigor with engineering pragmatism, aiming to solve societal-scale energy challenges.
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