Professor
Alpha Lab
School of Information Science and Technology
University of Sicence and Technology of China (USTC)
✉ Email: an_zhang at ustc.edu.cn
• Google Scholar Page • OpenReview Profile
Biography
I am currently a Professor at University of Science and Technology of China (USTC), where I lead the Alpha Lab. Prior to that, I was a postdoctoral research fellow in NExT++ Lab, National University of Singapore, working with Prof. Tat-Seng Chua. I obtained my Ph.D. from the National University of Singapore in 2021 and joined USTC in 2025. At AlphaLab, my colleagues, students, and collaborators work together to develop foundation models (large language models & diffusion models) and AI Agents, with an emphasis on understanding the capabilities and properties of next-generation general AI models. Our research is motivated by, and contributes to, real-world applications in personalization (e.g., recommender systems), education (e.g., smart campuses), and safety (e.g., LLM Safety).
- Personalization
- Tutorials [WWW 2025 Generative Recommendation Models] [CIKM 2025]
- LLM as Recommender [ReRe] [NeurIPS 2024 S-DPO] [SIGIR 2024 Agent4Rec]
- LLM enhanced Recommender [SIGIR 2025 AlphaFuse] [KDD 2025 LLM2Rec] [ICLR 2025 AlphaRec]
- Diffusion as Recommender [NeurIPS 2025 PrefGrow] [ICLR 2025 PrefDiff] [iDreamRec]
- Understanding and Abilitiies of Large Language Models
- Agentic [WWW 2024 Tutorial] [SIGIR 2024 Tutorial] [NeurIPS 2025 AutoRefine]
- Reasoning [NeurIPS 2025 AlphaReasoner]
- Safety [AlphaAlign] [NeurIPS 2025 SSA] [NeurIPS 2025 RSafe][AlphaSteer]
- Multimodality [ICLR 2025 FiSAO]
- [New!] 2023/10 One paper is accepted by TOIS'23! Thank all Collaborators!
Robust Collaborative Filtering to Popularity Distribution Shift. - 2023/10 One paper is accepted by EMNLP'23 Findings! Big congrats to Yaorui Shi and Other Collaborators!
ReLM: Leveraging Language Models for Enhanced Chemical Reaction Prediction. - 2023/09 Three papers are accepted by NeurIPS 23! Big congrats to Zhiyuan Liu, Junfeng Fang, and Other Collaborators!
Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss.
Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis.
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules. - 2023/07 Two papers are accepted by ACM MM'23! Big congrats to Yicong Li, Wei Ji, and Other Collaborators!
Redundancy-aware Transformer for Video Question Answering.
Online Distillation-enhanced Multi-modal Transformer for Sequential Recommendation. - 2023/05 One paper is accepted by KDD'23! Big congrats to Fangfu Liu and Other Collaborators!
Discovering Dynamic Causal Space for DAG Structure Learning. - 2023/01 One paper is accepted by WWW'23! Thank All Collaborators!
Invariant Collaborative Filtering to Popularity Distribution Shift. - 2023/01 One paper is accepted by ICLR'23! Thank All Collaborators!
Boosting Causal Discovery via Adaptive Sample Reweighting. - 2022/10 One paper is accepted by WSDM'23! Big congrats to Junfeng Fang and Other Collaborators!
Cooperative Explanations of Graph Neural Networks. - 2022/09 One paper is accepted by NeurIPS'22! Thank All Collaborators!
Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering. - 2022/05 One paper is accepted by ICML'22! Big congrats to Sihang Li and Other Collaborators!
Let invariant Rationale Discovery inspire Graph Contrastive Learning. - 2022/05 One papers is accepted by KDD'22! Big congrats to Yunshan Ma and Other Collaborators!
CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation. - 2022/04 One paper is accepted by TPAMI'22! Big congrats to Xiang Wang and Other Collaborators!
Reinforced Causal Explainer for Graph Neural Networks. - 2022/01 One paper is accepted by ICLR'22! Big congrats to Yinxin Wu and Other Collaborators!
Discovering invariant rationales for graph neural networks. - Review for ICML 2022, SIGKDD 2022, NeurIPS 2022, AAAI 2022, WSDM 2023, CVPR 2023, ICCV 2023, KDD 2023, ACM MM 2023, NeurIPS 2023, AAAI 2024, EMNLP 2024, WSDM 2024.
- Full Research Scholarship, National University of Singapore, 2016-2021
- Excellent Graduates, Southeast University, 2016
- Merit Student in Jiangsu Province, 2015
- Su Bote Outstanding Undergraduate Scholarship, Southeast University, 2014
- Merit Student in Southeast University, Southeast University, 2015/2014/2013
- 2023-Present: Research Fellow, NExT++, National University of Singapore
Supervisor: Prof Tat-Seng Chua & Prof Zhenkai Liang- 2021-2023: Research Fellow, NExT++, National University of Singapore
Supervisor: Prof Tat-Seng Chua- 2016-2021: PhD in Statistics, National University of Singapore
Supervisor: Prof Zehua Chen- 2012-2016: Bachelor in Mathematics and Applied Mathematics, Southeast University
Supervisor: Prof Jinde Cao & Prof Wenwu Yu - 2021-2023: Research Fellow, NExT++, National University of Singapore
Prospective PhD, Master, and Intern Students
I am actively looking for highly motivated PhD students, master students, and interns (undergraduate students) to work together on the trustworthiness AI, Personalization, and LLM-empowered Agents, and their applications in real-world scenarios. Please feel free to send me your CV and transcripts, if you have interest. We are also actively looking for opportunities in research, partnership and commercialization in exciting AI projects.