Yuhao Zhang

About Me

I am a Senior R&D Mechanical Engineer at Halliburton’s Advanced Controls Center of Excellence, where I develop advanced control and engineering solutions for drilling automation. I earned my Ph.D. in Mechanical Engineering from the University of Wisconsin–Madison under the guidance of Prof. Xiangru Xu. I received 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.

We will give an oral presentation at the 63rd IEEE Conference on Decision and Control (CDC) on Dec. 19, 2024

Jul 24, 2024

Reachability Analysis of Neural Network Control Systems With Tunable Accuracy and Efficiency

This paper introduces a novel tunable hybrid zonotope-based method for computing both forward and backward reachable sets of neural network control systems.

Jun 17, 2024

Presentation at 2023 IEEE CDC

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

Dec 15, 2023

Reachability Analysis and Safety Verification of Neural Feedback Systems via Hybrid Zonotopes

This paper presents novel hybrid zonotope-based methods for the reachability analysis and safety verification of neural feedback systems. Algorithms are proposed to compute the input-output relationship of each layer of a feed-forward neural network, as well as the exact reachable sets of neural feedback systems.

Jul 3, 2023

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

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

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

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

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