Yuhao Zhang

About Me

I am currently pursuing a Ph.D. in Mechanical Engineering at the University of Wisconsin–Madison, conducting research at the UW ARC Lab, under the guidance of Prof. Xiangru Xu. I earned my MSE in Mechanical Engineering from the University of Michigan–Ann Arbor in 2019, where I was mentored by Prof. Necmiye Ozay and Prof. Jean-Baptiste Jeannin. Prior to that, I completed my Bachelor of Engineering in Energy and Power Engineering at Peking University, with a double major in Economics from the National School of Development, in 2017.

I specialize in the theoretical analysis and application of autonomous and controlled systems and familiar with various programming languages, including MATLAB, Python, and C. My research focuses on control systems, incorporating optimization and machine learning techniques. The goal of my research is to develop principled analysis and control methodologies for building trustworthy autonomous intelligent systems.

I am actively seeking full-time opportunities beginning in early 2026. Feel free to contact me at yuhao.zhang2[at]wisc[dot]edu for connections and collaboration!

Backward Reachability Analysis of Neural Feedback Systems Using Hybrid Zonotopes
Backward Reachability Analysis of Neural Feedback Systems Using Hybrid Zonotopes

A novel approach for computing the exact backward reachable sets of neural feedback systems.

Jun 26, 2023

🎉 Our lab received the Honorable Mention Award in the research group category in Engineering Expo 2023
🎉 Our lab received the Honorable Mention Award in the research group category in Engineering Expo 2023

Apr 30, 2023

🎉 I received the Student Research Grants Competition (SRGC) Award from UW-Madison Graduate School

Apr 28, 2023

Safety Verification of Neural Feedback Systems Based on Constrained Zonotopes
Safety Verification of Neural Feedback Systems Based on Constrained Zonotopes

A novel set-based method is proposed to compute both exact and over-approximated reachable sets for neural feedback systems.

Jan 10, 2023

Presentation at 2022 IEEE CDC
Presentation at 2022 IEEE CDC

A novel set-based method is proposed to compute both exact and over-approximated reachable sets for neural feedback systems.

Dec 7, 2022

Control Barrier Function Meets Interval Analysis: Safety-Critical Control with Measurement and Actuation Uncertainties
Control Barrier Function Meets Interval Analysis: Safety-Critical Control with Measurement and Actuation Uncertainties

This paper presents a framework for designing provably safe feedback controllers for sampled-data control affine systems with measurement and actuation uncertainties.

Sep 5, 2022

🎉 I successfully passed the PhD Qualifying Examination

Sep 30, 2021

Falsification of a Vision-based Automatic Landing System
Falsification of a Vision-based Automatic Landing System

In this paper, we study falsification of an automatic landing system for fixed-wing aircraft using a camera as its main sensor.

Jan 4, 2021

Finding Matrix Sequences with a High Asymptotic Growth Rate for Linear Constrained Switching Systems
Finding Matrix Sequences with a High Asymptotic Growth Rate for Linear Constrained Switching Systems

This work investigates how to generate a sequence of matrices with an asymptotic growth rate close to the constrained joint spectral radius (CJSR) for constrained switching systems.

Sep 27, 2020

A Software Architecture for Autonomous Taxiing of Aircraft
A Software Architecture for Autonomous Taxiing of Aircraft

In this paper we describe a high-level software architecture for self-taxiing, and we identify its specific challenges.

Jan 5, 2020