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Wenbin Wan, Ph.D.
Department of Mechanical Science and Engineering
University of Illinois at Urbana-Champaign
Interests: Controls \(\cup\) Machine Learning \(\cap\) CPS
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[ Overview poster]

Safe Planning under Large Uncertainties

Inspired by the Miracle on the Hudson1, we aim to design a decision-making architecture that can quickly make a sequence of decisions for autonomous systems. We will integrate neuroscience, control theory, and machine learning by adequately leveraging their advantages towards having a safety guarantee under large uncertainties. More details

Safe Operation of Connected Vehicles in Unforeseen Environments

This project aims to develop a multi-level adaptive control architecture, where the proactive level leverages data over a cloud network to cope with unforeseen environmental uncertainties and support high-level decision making, while the reactive level uses machine learning and robust adaptive control to compensate for uncertainties. More details

Cyber-Physical Systems Security

Recent developments of Cyber-Physical Systems (CPS) and their safety-critical applications, such as power systems, critical infrastructures, transportation networks, and industrial control systems, have led to a renewed interest in CPS security. In this project, we aim to study and develop attack-resilient estimation and detection algorithms for CPS. More details