Wentao Tang
Chemical and Biomolecular Engineering
Assistant Professor
Chemical and Biomolecular Engineering
Engineering Building I (EB1) 2040
919.515.2328 wtang23@ncsu.edu WebsiteBio
Wentao Tang was born in Hunan Province, P.R. China. He was a process control engineer at Shell Global Solutions (U.S.) Inc., where he undertook multiple research projects for the development of Shell’s advanced process control software, prior to joining NC State University.
Education
Ph.D. Chemical Engineering Univeristy of Minnesota 2020
B.S. Chemical Engineering Tsinghua University 2015
B.S. Mathematics Tsinghua University 2015
Area(s) of Expertise
Wentao Tang's current research focuses on developing data-driven control algorithms that integrate nonlinear control theory with machine learning techniques, which avoid detailed dynamic modeling procedures and can be more flexible for systems with complex dynamics. He is also interested in derivative-free algorithms for optimization problems without explicit algebraic models, especially in how the solution of large-scale problems can benefit from the identification of underlying network topology, decomposition of networks into constituent subsystems and adoption of acceleration schemes.
Publications
- Machine learning‐based optimal control for colloidal self‐assembly , AIChE Journal (2026)
- Identification of noisy Koopman models , Computers & Chemical Engineering (2025)
- Koopman-Nemytskii Operator: A Linear Representation of Nonlinear Controlled Systems , arXiv (Cornell University) (2025)
- Learning the Integral Quadratic Constraints on Plant-Model Mismatch , arXiv (Cornell University) (2025)
- Process Resilience under Optimal Data Injection Attacks , AIChE Journal (2025)
- Data-Driven Bifurcation Analysis via Learning of Homeomorphism , Proceedings of Machine Learning Research (2024)
- Data-Driven Nonlinear State Observation using Video Measurements , IFAC-PapersOnLine (2024)
- Data‐driven nonlinear state observation for controlled systems: A kernel method and its analysis , The Canadian Journal of Chemical Engineering (2024)
- High-throughput design of complex oxides as isothermal, redox-activated CO2 sorbents for green hydrogen generation , Energy & Environmental Science (2024)
- Koopman Operator in the Weighted Function Spaces and its Learning for the Estimation of Lyapunov and Zubov Functions , arXiv (Cornell University) (2024)