CISE Seminar: Wei Xiao, Worcester Polytechnic Institute

Date: February 27, 2026
Time: 3:00pm – 4:00pm
Location: 665 Commonwealth Ave., CDS 1101

Wei Xiao
Assistant Professor in Robotics Engineering
Worcester Polytechnic Institue

Control Barrier Functions for Safe AI and Robotics

Safety is central to autonomous systems/robots since a single failure could lead to catastrophic results. In unstructured complex environments where system states and environment information are not available, the safety-critical control problem is much more challenging. In this talk, I will first discuss safety from a control theoretic perspective with Control Barrier Functions (CBFs). CBFs capture the evolution of the safety requirements during the execution of a control system and can be used to guarantee safety for all times due to their forward invariance. Next, this talk will introduce an approach for extending the use of CBFs to machine learning-based control, using differentiable CBFs that are end-to-end trainable and adaptively guarantee safety using environmental dependencies. These novel safety layers give rise to new neural network architectures such as what we have termed the BarrierNet and Adaptive BarrierNet. This talk will also show how we may employ CBFs for state-of-the-art machine learning systems, such as sequential models, diffusion generative models, and transformer-based large language models. The CBF method has been further applied to various robotic systems, both in simulations and in real robot experiments.

Wei Xiao is an assistant professor in the WPI robotics engineering department, and a research affiliate at MIT CSAIL, where he was a postdoctoral associate. Before that, he received his Ph.D. degree from the Boston University in 2021. His research interests include safety-critical control theory and trustworthy machine learning, with a particular emphasis on robotics and multi-agent systems. 

Faculty Host: Christos Cassandras
Student Host: Onur Okuducu