Asst Prof Wu Zhe was presented with the Outstanding Early Career Award (OECA) at the CDE Awards and Recognition ceremony on 21.4.2025
Dr. Wu’s group at the National University of Singapore develops cutting-edge machine-learning-based modeling, control and optimization algorithms to solve problems of important industrial considerations, including production profitability, process operational safety, and cybersecurity. He has made significant contributions to the advancement of AI-driven automation in complex industrial processes by addressing practical challenges such as data scarcity, curse of dimensionality, and model uncertainties in the chemical, pharmaceutical, and energy sectors. Since joining NUS in September 2021, Dr. Wu’s research has led to over 30 publications in leading chemical and process systems engineering journals such as AIChE Journal, Chemical Engineering Science, and Computers & Chemical Engineering. His works on developing online learning and physics-informed machine learning for predictive control of chemical processes have received considerable attention and are among the Top Downloaded Papers in AIChE Journal (2022-2023) and Chemical Engineering Research and Design (2023-2024).
Dr. Wu’s research has garnered international recognition. He has delivered several keynote presentations at top conferences such as PSE Asia (2022, 2024), and AIChE Annual Meeting (2023), and has chaired many sessions at international conferences, including AIChE Annual Meetings, IFAC World Congress, and American Control Conferences. He has also served as an Associate Editor for the American Control Conference and held editorial roles in Digital Chemical Engineering and ACS Chem & Bio Engineering Journal. He was listed among Stanford/Elsevier’s Top 2% Scientists.
Dr. Wu collaborates with leading companies, including Pfizer, GSK, MSD, Syngenta, and Applied Materials, to apply AI solutions to real-world manufacturing processes, accelerating the transition to next-generation manufacturing paradigms. Furthermore, Dr. Wu is equally committed to education and mentoring future leaders in the field. He taught the core course “Process Dynamics and Control” and developed several new courses such as “Machine Learning in Chemical Engineering” and “Process Safety Digitalization” to introduce the state-of-the-art technologies in chemical engineering education Through his innovative research, impactful industry collaborations, and dedication to teaching, Dr. Wu continues to shape the future of process systems engineering.
