I am currently a postdoctoral scholar in the Department of Computing + Mathematical Sciences at California Institute of Technology (Caltech), advised by Prof. Steven Low and Prof. Adam Wierman. I am honored to be a recipient of the Pioneer Postdoctoral Fellowship and PIMCO Postdoctoral Fellowship at Caltech. I obtained my Ph.D. in Electrical and Computer Engineering from the University of Washington, advised by Prof. Baosen Zhang.
My research interests lie broadly in control, machine learning and optimization for cyber-physical energy systems. Recently, I am developing structured control and learning methods with provably guarantees on safety-critical constraints and time-varying adaptations. I’m also working on efficient algorithums to overcome the challenges on sample complexity and explorations in learning for real-world applications (e.g., power systems).
Openings: I am excited to be joining the Department of Electrical and Computer Engineering at New York University (NYU) as a tenure-track Assistant Professor in September 2025. I am looking for self-motivated PhD students and postdoc starting in Fall 2025. If you are interested, feel free to email me (wenqicui@nyu.edu) with your CV and transcripts.
Download my CV.
PhD in Electrical and Computer Engineering, 2019-2024
University of Washington
MS in Electrical Engineering, 2016-2019
Zhejiang University
BEng in Electrical Engineering and Automation, 2012-2016
Southeast University
[2024/10] I will present our work Leveraging Predictions in Power System Frequency Control: an Adaptive Approach at 2024 INFORMS Annual Meeting in the session ME75 Advances in Data-driven Controls for Renewable Dominated Grids. Welcome to drop by our talks.
[2024/06] Disertation defense and ECE graduation in one day π. Heartfelt thanks to my advisor, PhD committee, family, friends, and everyone who has helped and supported me throughout this wonderful PhD journey π€.
[2023/12] I will present our work Leveraging Predictions in Power System Frequency Control: an Adaptive Approach at IEEE CDC 2023 in the session WeA16 Computational Techniques for Automation in Energy Systems. Welcome to drop by our talks.
[2023/12] I will present my research centers around structured control and learning for energy systems in the Meet the Faculty Candidates Poster Session at IEEE CDC 2023. Welcome to drop by our posters.
[2023/09] Our paper on Structured Neural-PI Control with End-to-End Stability and Output Tracking Guarantees is accepted in NeurIPS 2023.
Research experience include:
Research experience include:
Research experience include: