🏝️ About Me

Hello! I’m currently pursuing a Ph.D. in Electronic Engineering at Beihang University (BUAA). I hold a Master’s degree in Electronic Engineering from Shandong University (SDU), where I specialized in AI security, and a Bachelor’s degree in Mechanical Engineering and Automation from Qingdao University of Science and Technology (QUST).

Research Interests

My research aims to advance the sustainability, reliability, and efficiency of machine learning systems. Specifically, I focus on two core areas:

• 🛡️ Robustness: Strengthening model resilience against adversarial examples and other security threats.
• ⚡ Efficiency: Boosting learning efficiency with methods like dataset distillation, enabling smarter and more effective data utilization.

You can find my Curriculum Vitae here.

🔥 Recent Updates

• Mar. 2025: The BEARD black-box library was updated. Access the Project Page, Code, and Paper.
• Jan. 2025: Invited as a reviewer for TMLR 2025.
• Dec. 2024: Invited as a reviewer for ICML 2025.
• Nov. 2024: Preprint paper on BEARD, a benchmark for evaluating adversarial robustness in dataset distillation: Paper, Code, Leaderboard.
• Nov 2024: Honored to be selected as a Top Reviewer for NeurIPS 2024. Official Announcement.
• Oct. 2024: Invited as a reviewer for AISTATS 2025.
• Aug. 2024: Invited as a reviewer for ICLR 2025.
• Jun. 2024: Preprin paper on BACON, a new framework for dataset distillation: Project Page, Paper, Code.
• May. 2024: Invited as a reviewer for NeurIPS 2024.

📝 Publications

Journal

BEARD: Benchmarking the Adversarial Robustness for Dataset Distillation

Zheng Zhou, Wenquan Feng, Shuchang Lyu, Guangliang Cheng, Xiaowei Huang, Qi Zhao

Project Page | Code | Paper

Journal

BACON: Bayesian Optimal Condensation Framework for Dataset Distillation

Zheng Zhou, Hongbo Zhao, Guangliang Cheng, Xiangtai Li, Shuchang Lyu, Wenquan Feng, Qi Zhao

Project Page | Code | Paper

Journal

MVPatch: More Vivid Patch for Adversarial Camouflaged Attacks on Object Detectors in the Physical World

Zheng Zhou, Hongbo Zhao, Ju Liu, Qiaosheng Zhang, Liwei Geng, Shuchang Lyu, Wenquan Feng

Project Page | Paper

ICSI 2022

Adversarial Examples Are Closely Relevant to Neural Network Models - A Preliminary Experiment Explore

Zheng Zhou, Ju Liu and Yanyang Han

Project Page | Paper

🎖 Honors and Awards

• Oct 2022: Oral presentation at ICSI 2022 (International Conference on Swarm Intelligence).
• Sep 2023: Silver Award at ASCEND Competition for Re-ID.

📖 Education

• 2023.09 - Now, Ph.D. in Electronic Engineering, Beihang University (BUAA), Beijing, China, Advisor: Prof. Qi Zhao & Prof. Wenquan Feng.
• 2020.09 - 2023.06, M.Eng. in Electronic Engineering, Shandong University (SDU), Qingdao, China, Advisor: Prof. Ju Liu.
• 2016.10 - 2018.10, Visiting Student in Electronic Engineering, Technical University of Ilmenau (TU Ilmenau), Thuerigen, Germany.
• 2012.06 - 2016.09, B.Eng. in Mechanical Engineering and Automation, Qingdao University of Science and Technology (QUST), Qingdao, China.

🌟 Academic Service

Peer Review

I contribute to the academic community by reviewing papers for various prestigious journals and conferences, including:

Conference Reviewer

• NeurIPS 2024 (Top Reviewer)
• ICLR 2025
• AISTATS 2025
• ICML 2025
• NeurIPS 2025

Journal Reviewer

• Transactions on Machine Learning Research (TMLR)

💻 Work Experience

• 2018.10 - 2023.06, Embeded Software Engineer, Haier Group Corporation, Open Innovation Platform & GE Appliance Development Devision, China.