I am currently a Ph.D. candidate in the School of Data Science (SDS), the Chinese University of Hong Kong, Shenzhen (CUHKSZ) under the supervision of Professor Hongyuan Zha and Professor Baoyuan Wu. Previously, I received my Bachelor’s degree (rank No.1, first-class honor) in Electronic Information Engineering from the School of Science and Engineering (SSE), CUHKSZ.

Research

My research interests mainly lie in AI Security and Fairness, Computer Vision and Optimization, but also include Kernel Methods, Reinforcement Learning, and the application of Machine Learning in economics/marketing.

Projects and Awards

• Best Poster Award in The 3rd Doctoral & Postdoctoral Academic Forum
• 2023 Guo Tai Jun An Scholarship
• 2023 Duan Yong Ping Travel Award
• AIRS Talent of Ph.D. Research Program of Academic Year of 2020-2021

News

2024

• [2024-01-16] One paper gets accepted by ICLR 2024, in close collaboration with Zihao Zhu and Mingda Zhang.
• [2024-01-13] I receive the Best Poster Award in The 3rd Doctoral & Postdoctoral Academic Forum held by Shenzhen Research Institute of Big Data.

2023

• [2023-12-27] I receive the Guo Tai Jun An Scholarship to recognize my outstanding research achievements from 2020-2023.
• [2023-12-15] We release Defenses in Adversarial Machine Learning: A Survey, a comprehensive survey for defense methods in adversarial machine learning. The draft is available at this link.
• [2023-12-15] I receive the 2023 Duan Yong Ping Travel Award to recognize my outstanding research achievements in academic year 2022-2023.
• [2023-10-03] I was invited as a guest speaker for the tutorial Backdoor Learning: Recent Advances and Future Trends in ICCV 2023. Slides are available at this link.
• [2023-09-22] Two papers get accepted by NeurIPS 2023, in close collaboration with Mingli Zhu and Mingda Zhang.
• [2023-07-18] One paper gets accepted by ICCV 2023, in close collaboration with Mingli Zhu.
• [2023-04-21] BackdoorBench is updated to the 2nd version with more methods and analysis tools involved. The code and data are available at this link.
• [2023-01-20] One paper gets accepted by AISTATS 2023, in close collaboration with Jiayin Liu.

2022

• [2022-09-19] One paper gets accepted by NeurIPS 2022 Datasets and Benchmarks Track, in close collaboration with our team in SCLBD.
• [2022-06-28] We release BackdoorBench: a comprehensive benchmark of backdoor attack and defense methods. The code and data are available at this link.