Wenbin Wan

# Short Bio

Wenbin Wan is a Ph.D. candidate in Advanced Controls Research Laboratory with the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign (UofI).

He received his B.Sc. in Mechanical Engineering from the University of Missouri-Columbia in 2016 and received his first master's degree in Mechanical Engineering in 2017 and the second master's degree in Applied Mathematics in 2020 from UofI.

His main focus is developing estimation/machine learning algorithms for autonomous systems.

# Research Projects

### 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.

### 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.

### 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.