Duo Zhou

Hi, I'm a student of computer science at the University of Illinois Urbana-Champaign (UIUC). My research interests are in AI Safety, focusing on the theory and application of the following areas:

  • Trustworthy Machine Learning: I work on advancing machine learning robustness by addressing challenges like non-i.i.d. data and distribution shifts. My research also explores adversarial robustness, including neural network verification and attack & defense strategies.
  • Sequential Decision Making Under Uncertainty: I study robust and distributionally robust approaches to reinforcement learning, online learning, and optimal control. My goal is to develop methods that ensure reliable and optimal performance in uncertain and dynamic environments.
Email: duozhou2 at illinois dot edu Google Scholar GitHub
Profile photo of Duo Zhou

Selected Papers

* indicates contributed equally    † indicates corresponding author

Clip-and-Verify: Linear Constraint-Driven Domain Clipping for Accelerating Neural Network Verification

Duo Zhou*, Jorge Chavez*, Hesun Chen*, Grani A. Hanasusanto, Huan Zhang

Accepted by NeurIPS 2025

[paper] [code]

ShortageSim: Simulating Drug Shortages under Information Asymmetry

Mingxuan Cui*, Yilan Jiang*, Duo Zhou*, Cheng Qian, Yuji Zhang, Qiong Wang

preprint, 2025

[paper] [code]

Lookahead Branching for Neural Network Verification

Liam Davis, Duo Zhou

Accepted by Formal Methods in Computer-Aided Design 2025

[paper]

DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty

Mingxuan Cui*, Duo Zhou*†, Yuxuan Han, Grani A Hanasusanto, Qiong Wang, Huan Zhang, Zhengyuan Zhou

preprint, 2025

[paper] [code]

Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes

Duo Zhou, Christopher Brix, Grani A Hanasusanto, Huan Zhang

Advances in Neural Information Processing Systems 37, 29324--29353, 2024.

[paper] [code]

Distributionally robust path integral control

Hyuk Park, Duo Zhou, Grani A Hanasusanto, Takashi Tanaka

American Control Conference (ACC), pp. 1164-1171. IEEE, 2024.

[paper] [code]

An adaptive and dynamical neural network for machine remaining useful life prediction

Ruibing Jin*, Duo Zhou*, Min Wu, Xiaoli Li, Zhenghua Chen

IEEE Transactions on Industrial Informatics 20, no. 2 (2023): 1093-1102, 2023

[paper]

Selected Honors

  • The Winner for both Regular & Extended Track in VNN-COMP 2025.
  • The Winner for both Regular & Extended Track in VNN-COMP 2024.
  • First-Class Scholarship for the Graduating Class. 2021.
  • Meritorious Winner of Mathematical Contest in Modeling and Interdisciplinary Contest in Modeling. 2020.
  • Provincial First Prize, Contemporary Undergraduate Mathematical Contest in Modeling. 2019.

Selected Services

  • Reviewer: NeurIPS, ICLR, ICML, AAAI