Chao Huang's Webpage

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Chao Huang
Lecturer (Assistant Professor)
Department of Computer Science
University of Liverpool
Liverpool, UK
Email: chao.huang2 [AT] liverpool [DOT] ac [DOT] uk

I am now a lecturer in the department of Computer Science at the University of Liverpool,UK. I am also an adjunct assistant professor in the Department of Electrical and Computer Engineering at Northwestern University, US.

My research interests include design and verification of intelligent systems, of which the components involve machine learning techniques. Before joining Liverpool, I worked with Prof. Qi Zhu as a postdoc fellow, in the ECE department at Northwestern University. Prior to Northwestern, I received my B.S. and PhD in mathematics and applied mathematics and computer science from Nanjing University respectively. I also visited the Department of Computer Science at Aalborg University and was pleased to work with Prof. Kim G. Larsen.

For Prospective Students

I am looking for highly motivated students, who are interested in at least one of the following topics: cyber-physical systems, design automation, formal methods, machine learning. The students are expected to have a strong background in at least one of the following areas: computer science/engineering, electrical engineering, mathematics, statistics, physics.

Recent News

  • 2022.08 Our paper POLAR: A Polynomial Arithmetic Framework for Verifying Neural-Network Controlled Systems has been accepted by ATVA 2022.

  • 2022.03 Our paper Efficient Global Robustness Certification of Neural Networks via Interleaving Twin-Network Encoding has been accepted by DATE 2022 and received Best Paper Award!

  • 2022.02 Our paper Design-while-Verify: Correct-by-Construction Control Learning with Verification in the Loop has been accepted by DAC 2022.

  • 2022.01 Our paper Physics-Aware Safety-Assured Design of Hierarchical Neural Network based Planner has been accepted by ICCPS 2022.

  • 2021.07 Our paper Cross-Layer Adaptation with Safety-Assured Proactive Task Job Skipping has been accepted by EMSOFT 2021.

  • 2021.02 Our paper Cocktail: Learn a Better Neural Network Controller from Multiple Experts via Adaptive Mixing and Robust Distillation has been accepted by DAC 2021.

Education

  • Nanjing University: PhD, Computer science, 2011 - 2018

  • Nanjing University: B.S., Mathematics, 2007 - 2011

Work

  • Northwestern University, Evanston: Postdoc fellow, ECE, 2018 - present