Zhengang Zhong
Data-Driven Distributionally Robust Control
Zhengang is a PhD candidate at Imperial College London. His PhD research is about data-driven distributionally robust model predictive control.Prior to his PhD research, he holds a Diplom-Ingenieur in Mechatronics from Technische Universität Dresden. His research interests include data-driven optimal control, scientific machine learning, and distributionally robust optimisation.
Dr. Ehecatl Antonio del Rio Chanona
Principal Investigator of OptiML
Antonio del Rio Chanona is the head of the Optimisation and Machine Learning for Process Systems Engineering group based in thee Department of Chemical Engineering, as well as the Centre for Process Systems Engineering at Imperial College London. His work is at the forefront of integrating advanced computer algorithms from optimization, machine learning, and reinforcement learning into engineering systems, with a particular focus on bioprocess control, optimization, and scale-up. Dr. del Rio Chanona earned his PhD from the Department of Chemical Engineering and Biotechnology at the University of Cambridge, where his outstanding research earned him the prestigious Danckwerts-Pergamon award for the best PhD dissertation of 2017. He completed his undergraduate studies at the National Autonomous University of Mexico (UNAM), which laid the foundation for his expertise in engineering.