• I am a Professor in the School of Artificial Intelligence and Data Science at the University of Science and Technology of China (USTC). My research focuses on large-scale data mining, trustworthy and secure AI & systems, with an emphasis on machine learning techniques and real-world applications, including graph mining and learning, ML privacy, foundation models, FinTech, and learning systems. My work has been published in top conferences (e.g., ICML, NeurIPS, ICDE, WWW, ACM MM) and journals (e.g., TKDE, TKDD, TOSEM). Additionally, I serve as a program committee member for leading international conferences such as ICML, CVPR, WWW, SIGKDD, NeurIPS, and IJCAI, and as a reviewer for prestigious journals, including TKDE, TDSC, TKDD, KAIS, and TNNLS.

• I earned my Ph.D. in Computer Science from the Institute of Computing Technology, Chinese Academy of Sciences, under the supervision of Prof. Xueqi Cheng and in collaboration with Prof. Shenghua Liu. I received my B.Eng. in Computer Science and Technology at Beijing Jiao Tong University. Previously, I was a research fellow at the Institute of Data Science (IDS), National University of Singapore, working with Prof. Bryan Hooi and Prof. See-Kiong NG.

• [Curriculum Vitae] and [Google Scholar]

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1. General Hiring Requirements:
   • Passion, determination, and preservation to conduct high-quality research.
   • Good communication and collaboration skills.
   • Strong coding ability (C/C++ or Python).
2. Hiring tenure-track faculty and postdocs in DM/ML:
   • With a Ph.D. degree (or soon to graduate)
   • At least three first-author papers on top-tier conferences
3. Hiring PhD students from USTC and masters:
   • English (CET-6 score 500+, or equal levels)
   • Strong mathematics foundations (calculus, linear algebra, optimization, information theory, probability and statistics, etc.)
4. Hiring master’s students and undergraduate interns:
   • Good foundation in mathematics (calculus, linear algebra, probability and statistics)
   • Experience in high-level competitions (e.g., ACM-ICPC, KDD-Cup) or top-tier publications will be preferred.

I am looking for self-motivated undergraduate interns, master’s students, and Ph.D. students with solid mathematical backgrounds and coding skills. Feel free to drop me an email with your CV if interested. I am also open to discussions and collaborations on the topics mentioned above!

What’s New

• Our paper "Balanced Distribution Adaptation for Transfer Learning" has been selected to receive the ICDM 2026 10-Year Highest-Impact Paper Award!
• Three papers accepted by NeurIPS 2026. Congrats to all authors!
• One paper accepted by ACM MM 2026.
• One paper accepted by ICLR 2026.
• Our paper “FAVDisco: Modeling and Discovering File Access Vulnerabilities” is accepted to TOSEM 2025.
• Our paper “Rethinking Machine Unlearning in Image Generation Models” is accepted to CCS 2025,
• Our paper “Interrelated Dense Subgraph Detection in Multilayer Networks” is accepted to ICDE 2025.
• Our paper “ID3: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition” is accepted to NeurIPS 2024.
• Our paper “One-Shot Sequential Federated Learning for Non-IID Data by Enhancing Local Model Diversity” is accepted to ACM MM 2024.
• Our paper “Macro Adversarial Training to Learn Representations That are Robust to Word-Level Attacks” is accepted to NAACL 2024.
• Aug. 29, 2020, our paper “SpecGreedy: Unified Dense Subgraph Detection” was selected as the Best Student DM paper award for ECML-PKDD 2020.

Experiences

• Professor, University of Science and Technology of China, Feb. 2025 - Present
• Postdoc Research Fellow, National University of Singapore, Oct. 2020 - Jan. 2025.

Last updated in Oct. 2026.