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 employment starting in 2025. 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