Wenqi Cui

Dr. Wenqi Cui is an incoming tenure-track Assistant Professor at New York University's Tandon School of Engineering, Department of Electrical and Computer Engineering, joining in Fall 2025. Currently, she is a Postdoctoral Scholar at California Institute of Technology's Department of Computing + Mathematical Sciences, advised by Prof. Steven Low and Prof. Adam Wierman. Her research focuses on control, machine learning, and optimization for sustainable power systems and cyber-physical systems, emphasizing safety-critical AI solutions. Cui holds a PhD from the University of Washington (2024), an MS from Zhejiang University (2019), and a BEng from Southeast University (2016).

Her work bridges theoretical foundations and practical applications, addressing challenges in decarbonizing energy systems. Notable contributions include structured neural-PI control with stability guarantees, reinforcement learning for frequency control, and efficient algorithms for power system dynamics. Cui has received prestigious fellowships like the Pioneer and PIMCO Postdoctoral Fellowships and was named a Rising Star in EECS (2022) and Cyber-Physical Systems (2023).

• Education:
  • PhD in Electrical and Computer Engineering, University of Washington (2019–2024)
  • MS in Electrical Engineering, Zhejiang University (2016–2019)
  • BEng in Electrical Engineering and Automation, Southeast University (2012–2016)
• Research Interests:
  • Control Theory & Optimization
  • Machine Learning & Reinforcement Learning
  • Power System Dynamics & Decarbonization
  • Cyber-Physical Systems
• Awards:
  • Pioneer Postdoctoral Fellowship (Caltech)
  • PIMCO Postdoctoral Fellowship (Caltech)
  • Rising Stars in EECS (2022)
  • Rising Stars in Cyber-Physical Systems (2023)

Her research group at NYU aims to develop algorithms for safe, robust AI-driven solutions in energy systems. Cui is actively recruiting PhD students and postdocs for Fall 2025.