Wenqi Fan
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Assistant Professor Email: wenqifan03(at)gmail(dot)com, wenqi.fan(at)polyu(dot)edu(dot)hk Office: PQ743, Mong Man Wai Building, Hung Hom, Kowloon, Hong Kong SAR. |
Short Bio
Dr. Wenqi Fan is currently an Assistant Professor of the Department of Computing (COMP) & Department of Management and Marketing (MM), The Hong Kong Polytechnic University (PolyU). Before that, he was a Research Assistant Professor and a Postdoctoral Fellow at PolyU (2020-2023). He received his Ph.D. degree in computer science from the City University of Hong Kong (2017-2020), under the supervision of Prof. Qing LI and Prof. Jianping WANG. From 2018 to 2021, he was a research scholar of Data Science and Engineering (DSE) Lab at Michigan State University (MSU), under the supervision of Prof. Jiliang Tang. He is recognized as the AI 2000 Most Influential Scholar Honorable Mention (2022, 2023, 2024) , and one of the World’s Top 2% Scientists by Stanford University (2023, 2024). His research has been supported by multiple government research fund agencies, including Hong Kong Research Grants Council (RGC-GRF), National Natural Science Foundation of China (NSFC), Hong Kong Innovation and Technology Commission (ITF), etc. He has published his research in highly ranked journals and top conference proceedings [Google Scholar].
>>> Welcome to contact me if you are interested in interdisciplinary research (collaborating with our group) using Data Mining/Machine Learning/Artificial Intelligence!
Research Interests [Google Scholar]
Data Mining, Machine Learning, and Artificial Intelligence, with a particular focus on:
Recommender Systems (RecSys) and Management Information Systems (MIS)
Large Language Models (LLMs)
Trustworthy AI: Adversarial Attacks & Robustness; Fairness; Explainability, etc.
Graph Machine Learning: Graph Neural Networks; Graph Foundation Models
AI/ML/DM + X: Business; Science.
>>>Openings: Our research group are actively recruiting self-motivated Postdoc, Ph.D. students, Dual PhD Degree students, MPhil/Msc, and Research Assistants, etc. Visiting scholars, interns, and self-funded students are also welcome. Send me an email if you are interested (Year-round Recruitment). [Please click here for position details.]
>>> Call for Papers (Special Topics Track@WISE 2024): Graph Machine Learning on Web and Social Media: Trends, Challenges, and Applications
International Web Information Systems Engineering conference (also known as the WISE conference), 2024.
Submission Deadline: 30 July, 2024. Location: Doha Qatar. Conference Dates: 2-5 December 2024.
News
- 2024
09/2024: One paper (Multi-agent Attacks for Black-box Social Recommendations) got accepted by ACM TOIS 2024. Congratulations to Shijie.
09/2024: Our new preprint “SSD4Rec: A Structured State Space Duality Model for Efficient Sequential Recommendation” is online.
08/2024: Check out our survey on A Survey of Mamba.
06/2024: Gratefully receive a grant (RGC-GRF) as the PI to support our research on Large Language Models and Recommender Systems. Multiple PhD/Postdoc/RA positions are available (Year-round Recruitment). [Please click here for position details.]
06/2024: Our new preprint “TokenRec: Learning to Tokenize ID for LLM-based Generative Recommendation” is online.
05/2024: Our survey paper&tutorial (A Survey on RAG Meets LLMs: Towards Retrieval-Augmented Large Language Models) got accepted by KDD 2024. Congratulations to Yujuan, Liangbo and Shijie. [Website]
05/2024: One paper got accepted by KDD 2024. Congratulations to Liangbo and Shijie.
05/2024: Gratefully receive a grant (Intra-Faculty Interdisciplinary Project) as the PC/Co-PI to support our research.
05/2024: Check out our survey on A Survey on RAG Meets LLMs: Towards Retrieval-Augmented Large Language Models.
04/2024: Check out our survey on Graph Machine Learning in the Era of Large Language Models (LLMs).
04/2024: Our survey paper (“Recommender Systems in the Era of Large Language Models (LLMs)”) got accepted by IEEE TKDE 2024.
04/2024: Our tutorial on “Recommender Systems in the Era of Large Language Models (LLMs)” is accepted by IJCAI 2024. Congratulations to Yujuan, Shijie, and Liangbo. More
03/2024: I was recognized as the “2024 AI 2000 Most Influential Scholar Honorable Mention” in the field of IR and Recommendation by the AMiner.
03/2024: One demo paper (“FashionReGen: LLM-Empowered Fashion Report Generation”) and one short paper (“Interpretation-Empowered Neural Cleanse for Backdoor Attacks”) got accepted by ACM TheWeb Conference (WWW) 2024. Congratulations to Yujuan and Liangbo.
01/2024: Two papers (“Linear-Time Graph Neural Networks for Scalable Recommendations” and “Fast Graph Condensation with Structure-based Neural Tangent Kernel”) got accepted by ACM TheWeb Conference (WWW) 2024. Congratulations to Jiahao ZHANG, Lin WANG, and Jiatong LI.
01/2024: One paper (“Revisiting Link Prediction: A data perspective”) got accepted by ICLR 2024.
- 2023
12/2023: Two students received PolyU Presidential PhD Fellowship Scheme (PPPFS) to support their PhD study.
11/2023: Our workshop on “Large Language Models (LLMs) for Graph Learning” is accepted by The Web Conference 2024 (WWW 2024). More
09/2023: Our tutorial on “Recommender Systems in the Era of Large Language Models (LLMs)” is accepted by ICDM 2023. Congratulations to Jiatong, Zihuai, and Yunqing. More
07/2023: Our new preprint “Certified Robustness for Large Language Models with Self-Denoising” is online.
07/2023: Our new preprint “Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs” is online.
07/2023: Our new preprint “Recommender Systems in the Era of Large Language Models (LLMs)” is online.
06/2023: Gratefully receive a grant (RGC-GRF) as the Co-I to support our research.
06/2023: Our new preprint “Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective” is online.
05/2023: Our tutorial on “Trustworthy Recommender Systems: Foundations and Frontiers” is accepted by KDD 2023 [Website].
04/2023: Our tutorial on “Trustworthy Recommender Systems: Foundations and Frontiers” is accepted by IJCAI 2023 [Website].
04/2023: Our survey paper (“Generative Diffusion Models on Graphs: Methods and Applications”) got accepted by IJCAI 2023. Congratulations to Chengyi, Yunqing, and Jiatong for their first paper with PolyU.
04/2023: Our paper (“Adversarial Attacks for Black-box Recommender Systems via Copying Transferable Cross-domain User Profiles”) got accepted by IEEE TKDE 2023.
04/2023: One paper got accepted by SIGIR 2023.
02/2023: Our new preprint “Generative Diffusion Models on Graphs: Methods and Applications” is online.
01/2023: One paper (Fairly Adaptive Negative Sampling for Recommendations) got accepted by The Web Conference (WWW’2023). Congratulations to Xiao Chen for his first paper with PolyU.
- 2022
12/2022: Our tutorial on “Trustworthy Recommender Systems” is accepted for the Web Conference (WWW’2023) [Website].
11/2022: One paper (Jointly Attacking Graph Neural Network and its Explanations) got accepted by ICDE’2023.
11/2022: Our tutorial on “AutoML for Deep Recommender Systems: Fundamentals and Advances” is accepted for the WSDM Conference (WSDM’2023) [Website].
09/2022: Our new preprint “A Comprehensive Survey on Trustworthy Recommender Systems” is online.
09/2022: One paper (Fairness Reprogramming) got accepted by NeurIPS’2022.
08/2022: One paper (Identifying The Kind Behind SMILES - Anatomical Therapeutic Chemical Classification using Structure-Only Representations) got accepted by BIB’2022 (Impact Factor: 13.994).
08/2022: One paper (Disentangled Contrastive Learning for Social Recommendation) got accepted by CIKM’2022. Congratulations to Jiahao WU for his first paper with PolyU.
07/2022: Invited to serve as the (Senior) PC Member of AAAI’2023 and ICLR’2023.
06/2022: Gratefully receive two grants (RGC-GRF and Internal Research Fund@PolyU) as the PI to support our research on Graph Neural Networks. Multiple PhD/Postdoc/RA positions are available (Year-round Recruitment). [Please click here for position details.]
05/2022: One paper (Knowledge-enhanced Black-box Attacks for Recommendations) got accepted by KDD’2022. Congratulations to my incoming PhD student Jingfan for his first paper with PolyU.
05/2022: Our survey paper (Trustworthy AI: A Computational Perspective [Arxiv]) is accepted by ACM TIST. In the survey, we examine SIX dimensions in achieving trustworthy AI, including (i) Safety & Robustness, (ii) Non-discrimination & Fairness, (iii) Explainability, (iv) Privacy, (v) Accountability & Auditability, and (vi) Environmental Well-Being, and review the latest research works in each dimension from a computational perspective.
04/2022: Our new preprint “Automated Machine Learning for Deep Recommender Systems: A Survey” is online.
04/2022: 1 paper (Graph Trend Filtering Networks for Recommendation [Arxiv] [Code-Pytorch]) got accepted by SIGIR’2022.
03/2022: I am invited to serve as a reviewer for NeurIPS 2022.
03/2022: I was recognized as “2022年AI 2000人工智能最具影响力学者提名奖！” (“2022 AI 2000 Most Influential Scholar Honorable Mention” in Information Retrieval and Recommendation) based on the Tsinghua-AMiner academic data. 榜单链接Link.
- 2021
12/2021: Our tutorial on “Trustworthy AI: A Computational Perspective” is accepted for is accepted for the Web Conference (WWW’22) [Website].
12/2021: Our tutorial on “Automated Machine Learning for Recommendations: Fundamentals and Advances” is accepted for the Web Conference (WWW’22) [Website].
12/2021: One paper got accepted by AAAI’22.
11/2021: Invited to serve as the Senior PC Member of KDD’22.
09/2021: 1 paper got accepted by ICDM’2021.
07/2021: Our new preprint “Trustworthy AI: A Computational Perspective” is online.
07/2021: Our tutorial on “Trustworthy AI: A Computational Perspective” is accepted for ICAPS 2021.
06/2021: Invited to serve as PC Member for ICLR 2020 and WSDM 2022.
06/2021: A Chinese Survey on Graph Nerual Networks based Recommender Systems, “综述：基于图学习的推荐系统”.
05/2021: Our paper “AutoLoss: Automated Loss Function Search in Recommendations” is accepted by KDD 2021.
04/2021: Invited to serve as PC member for NeurIPS/CIKM 2021.
04/2021: Our tutorial on “Deep Learning for Recommendations: Fundamentals and Advances” is accepted to be held in IJCAI 2021.
- 2020
12/2020: Our tutorial “Deep Recommender System: Fundamentals and Advances” has been accepted by WWW 2021.
12/2020: Invited to serve as PC member for ICML 2021.
11/2020: Invited to serve as PC member for KDD 2021.
10/2020: One full paper got accepted by ICDE 2021.
09/2020: One paper got accepted by COLING 2020 about Fairness/bias in Dialogue Systems.
08/2020: Invited to serve as PC member for AAAI2021 and IJCAI2021.
06/2020: One paper “A Graph Neural Network Framework for Social Recommendations” is accepted by IEEE TKDE.
05/2020: Preprint “Attacking Black-box Recommendations via Copying Cross-domain User Profiles” [Arxiv]
03/2020: SDM2020 Doctoral Forum accepted “Deep Social Recommendations”.
03/2020: Awarded SDM2020 Student Travel Award with funds from SIAM.
- 2019
12/2019: Two papers are accepted by SDM 2020.
12/2019: Invited to serve as PC member for IJCAI 2020 and AI4EDU 2020.
10/2019: Preprint of our paper “Does Gender Matter? Towards Fairness in Dialogue Systems” is released [link].
10/2019: Our paper “Epidemic Graph Convolutional Network” is accepted by WSDM 2020 (Preprint coming soon!).
06/2019: Our paper “Deep Social Collaborative Filtering” is accepted by RecSys 2019.
06/2019: Received the IJCAI 2019 Student Travel Award and will serve as volunteer.
05/2019: Our paper “Deep Adversarial Social Recommendation” is accepted by IJCAI 2019.
01/2019: Our paper “Graph Neural Networks for Social Recmmendation” is accepted by WWW 2019.