Yixuan Wang
Hi, welcome to my personal page!
I received my Ph.D. degree in the Computer Engineering at Northwestern University in June 2024, supervised by Prof. Qi Zhu. I also work closely with Prof. Chao Huang from Unversity of Southampton, UK. My research interestes include machine learning and formal methods, with the consideration of safety, stability, robustness and correctness for cyber-physical systems. My Ph.D. thesis is “Safety-Assured Autonomy for Learning-Enabled Cyber-Physical Systems”.
Prior to Northwestern, I received my B.E. from Tsinghua University in 2018.
E-mail: wangyixu14@gmail.com
My research overview, Curriculum Vitae, Google Scholar, Github
Recent News
2024.09 Paper Variational Delayed Policy Optimization is accepted as a spotlight paper to NeurIPS 2024.
2024.07 Paper Kinematics-aware Trajectory Generation and Prediction with Latent Stochastic Differential Modeling is accepted to IROS 2024.
2024.07 Paper Case Study: Runtime Safety Verification of Neural Network Controlled System is accepted to Runtime Verification 2024.
2024.06 I received my Ph.D. degree from Northwestern University, with a best Computer Engineering Ph.D. Thesis Award.
2024.05 Our paper Boosting Long-Delayed Reinforcement Learning with Auxiliary Short-Delayed Task is accepted to ICML 2024.
2024.04 I passed my Ph.D. defense exam! The slide presentation can be found here.
2024.03 Paper State-wise Safe Reinforcement Learning with Pixel Observations has been accepted to L4DC.
2024.03 Paper Empowering Autonomous Driving with Large Language Models: A Safety Perspective is accepted by ICLR 2024 Workshop on LLM Agents.
2023.12 Paper REGLO: Provable Neural Network Repair for Global Robustness Properties has been accepted by AAAI 2024.
2023.10 Paper POLAR-Express: Efficient and Precise Formal Reachability Analysis of Neural-Network Controlled Systems is accepted to IEEE TCAD.
2023.08 Book chapter Safety-Assured Design and Adaptation of Connected and Autonomous Vehicles is online.
2023.06 Paper Safety-Assured Speculative Planning with Adaptive Prediction is accepted to IROS 2023.
2023.05 I will give a talk about our ICCPS and ICML work to the 6th IEEE International Workshop on Design Automation for Cyber-Physical Systems (DACPS), which will mainly cover our recent ICML and ICCPS paper, where we developed a differentiable joint-learning bi-level optimization framework for safe RL.
2023.04 Paper Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments has been accepted to ICML 2023, see u in Hawaii this Summer!
2023.03 I passed the Ph.D. Prospectus Exam!
2023.01 Paper Joint Differentiable Optimization and Verification for Certified Reinforcement Learning is accepted by ICCPS 2023.
Working Experience
Aurora Innovation, Mountain View, CA, USA, 2023.07 - 2023.09, Machine Learning Engineering Intern
Bosch USA, Sunnyvale, CA, USA, 2023.03 - 2023.06, Machine Learning Engineering Intern
Ford Motor Company, Dearborn, MI, USA, 2021.06 - 2021.09, Research Intern
Sensetime, Shenzhen, China 2019.04 - 2019.08, Machine Learning Engineering Intern
Mech-Mind Robotics, Beijing, China, 2017.12 - 2018.02, Software Development Engineering Intern
Services
Reviewer for AAAI, NeurIPS, ICML, ICLR, RAL, CDC, IV, IOT Journal, etc
ICCPS 2024 Poster/Demo PC member
ICCPS 2024 Artifact Evaluation PC member
Teaching
Teaching Assistant for ELEC_ENG 373, 473 Deep Reinforcement Learning from Scratch, Spring 2022.
Awards
Best Computer Engineering Ph.D. Thesis Award, Northwestern University, 2024.
Terminal Year Fellowship, Nothwestern University, 2023.
Best Paper Candidate, ICCAD 2020.
Northwestern Univerisity Ph.D. Fellowship, 2019-2020.
Academic Excellence Award(top 10%), Tsinghua University, in all the undergraduate years(2014-2018).
National Scholarship(top 2%), 2016.
Outstanding Undergraduate Students(top 2%), Tsinghua Univerisity, 2018.
Outstanding Undergraduate Students of Beijing(top 5%), 2018.