Email: shimiaol@andrew.cmu.edu
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I am a PhD candidate in Electrical and Computer Engineering (ECE) at Carnegie Mellon University, advised by Prof. Larry Pileggi. Previously, I received my B.E. degree in electrical engineering from Tianjin University. My research is a novel combination of system models, optimization and machine learning tools to improve resiliency, for power systems in my past work, and broadly for the next-generation smart infrastructures in the future. My research has been part of the SUGAR toolbox which is a power grid analysis tool commercialized by Pearl Street Technologies, Inc. My work has also been recognized by the best paper award in the 2021 PES general meeting, and selected in 2023 Microsoft Accelerate Foundation Models Research Initiative.
Currently, my work focuses on [Physics-ML synergy] Physics-ML Synergy to Improve the Resiliency of Power Grid. Physics-ML synergy motivates a synergy architecture for state-of-the-art physical solvers and data-driven models to interconnect and merge their benefits. It enriches system modeling with ML-generated prior knowledge to advance robustnesss against modern cyberattacks. I am on the job market looking for tenure-track assistant professor positions. Please kindly reach out to me if there is any opportunity that fits me!
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