Chin-Yao Chang is a researcher at NREL. He received a B.S. degree in physics from National Taiwan University in 2010, and a Ph.D. degree in electrical and computer engineering from the Ohio State University in 2016. His research is mainly on control and optimization with applications to power systems and microgrids. Recent research focus areas are measurement-based algorithms, optimal power flow, and quantum computing. His research draws diverse methods from control theory, optimization, graph theory, integer programming, and networked control systems.

Education

Ph.D., Electrical and Computer Engineering, The Ohio State University

B.S., Physics, National Taiwan University

Professional Experience

Postdoctoral researcher, University of California, San Diego (2016–2018)

Associations and Memberships

Member, Institute of Electrical and Electronics Engineers (IEEE)

Featured Work

On Quantum Computing for Mixed-integer Programming, IEEE Transactions on Quantum Engineering (2021)

Online Data-enabled Predictive Control, Automatica (2021)

Distributed Approximate Newton Algorithms and Weight Design for Constrained Optimization, Automatica (2019)

Saddle-flow Dynamics for Distributed Feedback-based Optimization, IEEE Control Systems Letters (2019)

Awards and Honors

NREL President's Award (2019)