I am a Professor (博导) in University of Science and Technology of China. I received B.Eng. from Beihang University in July 2015 and PhD from National University of Singapore in August 2019. I have about 200 publications appeared in several top conferences such as SIGIR, SIGKDD, WWW, ACL, NeurIPS, ICML, and ICLR, as well as journals including Cell Reports, Cell Systems, TKDE, TOIS, and TPAMI. I received the Best Paper Honourable Mention in SIGIR 2021 and Best Poster Award in WWW 2018. My research interests include information retrieval, data mining, and multi-media analytics, particularly in machine learning techniques and applications such as large language model, causal inference, graph neural networks, recommender systems, AI4LifeScience, and FinTech. Moreover, I have served as the SAC/AC or SPC/PC-member for top-tier conferences including SIGIR, WWW, SIGKDD, NeurIPS, ICLR, ICML, ACL, and the invited reviewer for prestigious journals such as TOIS, TKDE, TPAMI, TNNLS, JASA, and Nature Sustainability.

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0. The 6th ACM International Conference on AI in Finance:
- ICAIF‘25, Singapore
- Call for Papers

1. Hiring tenure-track faculties and postdocs in NLP/IR/DM/AI4Science. Requirements:
- With PhD degree (or graduate soon)
- At least three first-author papers on tier-1 conferences
We provide competitive salary, sufficient funding and student supports, and good career opportunities.

2. Hiring PhD students from USTC and masters. Requirements:
- Strong code ability (C/C++ or Python)
- English (CET-6 score 500+ or equal levels or proficient in using ChatGPT or similar tools)
- Determination to do high-quality research.

3. Hiring undergraduate interns. Requirements:
- Strong code ability (C/C++ or Python)
- Determination to do high-quality research or interested in practical applications
- Experience in high-level competitions (e.g., ACM-ICPC and KDD-Cup) will be considered.

I hope every student can receive the core ability of systematically analyzing and solving research/technical problems, meanwhile, have a colorful and healthy life during the study in my group. I encourage students to be communicative and active in the group. I support various group activities, especially sports like badminton, jogging, and basketball. Meanwhile, I will try my best to create internship or visiting opportunities for students seeking such experience.

Tutorials, Workshops, and Surveys

Tutorials:

pdf	Large Language Models for Recommendation: Progresses and Future Directions SIGIR‘25, SIGIR’24, WWW‘24, SIGIR-AP’23 Slides

pdf	Causal Recommendation: Progresses and Future Directions SIGIR‘23, WWW’22 Slides

pdf	Bias Issues and Solutions in Recommender System WWW‘21, RecSys’21 Slides

Workshops:

pdf	Workshop on Personal Intelligence with Generative AI WWW'25, WWW'24, CIKM'23 Website

pdf	Workshop on Financial Information Retrieval SIGIR'25, SIGIR'20 Website

Surveys:

pdf	Personalized generation in large model era: A survey Xu, Yiyan, Jinghao Zhang, Alireza Salemi, Xinting Hu, Wenjie Wang, Fuli Feng, Hamed Zamani, Xiangnan He, and Tat-Seng Chua ACL'25

pdf	A survey of generative search and recommendation in the era of large language models Li, Yongqi, Xinyu Lin, Wenjie Wang, Fuli Feng, Liang Pang, Wenjie Li, Liqiang Nie, Xiangnan He, and Tat-Seng Chua arXiv (2024)

pdf	Negative Sampling in Recommendation: A Survey and Future Directions Ma, Haokai, Ruobing Xie, Lei Meng, Fuli Feng, Xiaoyu Du, Xingwu Sun, Zhanhui Kang, and Xiangxu Meng arXiv (2024)

pdf	Causal inference in recommender systems: A survey and future directions Gao, Chen, Yu Zheng, Wenjie Wang, Fuli Feng, Xiangnan He, and Yong Li ACM TOIS (2024)

pdf	Bias and debias in recommender system: A survey and future directions Chen, Jiawei, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang, and Xiangnan He ACM TOIS (2023)

Selected Publications in Recent 3 Years

I usually forgot to update my profile timely, please find my latest work at Google Scholar

AI for Life Science and Medicine:

pdf	Hierarchical progressive learning for zero-shot peptide-HLA binding prediction and automated antigenic peptide design Zhu, Xinyuan, Jiadong Lu, Xinting Hu, Tengchuan Jin, Shan Lu, and Fuli Feng Cell Reports (2025)

pdf	FlowDesign: Improved design of antibody CDRs through flow matching and better prior distributions Wu, Jun, Xiangzhe Kong, Ningguan Sun, Jing Wei, Sisi Shan, Fuli Feng, Feng Wu, Jian Peng, Linqi Zhang, Yang Liu, and Jianzhu Ma Cell Systems (2025)

pdf	Improving the Hit Rates of Virtual Screening by Active Learning from Bioactivity Feedback Deng, Xun, Junlong Liu, Zhike Liu, Jiansheng Wu, Fuli Feng, Jieping Ye, and Zheng Wang Journal of Chemical Theory and Computation (2025)

pdf	Improving the Hit Rates of Virtual Screening by Active Learning from Bioactivity Feedback Deng, Xun, Junlong Liu, Han Zhong, Fuli Feng, Chen Shen, Xiangnan He, Jieping Ye, Zheng Wang ICML'24

pdf	Improving the Hit Rates of Virtual Screening by Active Learning from Bioactivity Feedback Deng, Xun, Junlong Liu, Han Zhong, Fuli Feng, Chen Shen, Xiangnan He, Jieping Ye, Zheng Wang ICML'24

pdf	Leave no patient behind: Enhancing medication recommendation for rare disease patients Zhao, Zihao, Yi Jing, Fuli Feng, Jiancan Wu, Chongming Gao, and Xiangnan He SIGIR'24

pdf	Improving prostate cancer risk prediction through partial AUC optimization Zhu, Xinyuan, Xiaohan Ren, Wentao Shi, Changming Wang, Xuehan Liu, Yuqing Liu, Tao Tao, and Fuli Feng WWW'24 (Health Day)

pdf	Test-Time Training for Deep MS/MS Spectrum Prediction Improves Peptide Identification Ye, Jianbai, Xiangnan He, Shujuan Wang, Meng-Qiu Dong, Feng Wu, Shan Lu, and Fuli Feng Journal of Proteome Research (2023)

pdf	ADRNet: A generalized collaborative filtering framework combining clinical and non-clinical data for adverse drug reaction prediction Li, Haoxuan, Taojun Hu, Zetong Xiong, Chunyuan Zheng, Fuli Feng, Xiangnan He, and Xiao-Hua Zhou RecSys'23 Short

Generative AI:

pdf	Self-improvement Towards Pareto Optimality: Mitigating Preference Conflicts in Multi-Objective Alignment Li, Moxin, Yuantao Zhang, Wenjie Wang, Wentao Shi, Zhuo Liu, Fuli Feng, and Tat-Seng Chua ACL'25 (Findings)

pdf	Disentangling Reasoning Tokens and Boilerplate Tokens for Language Model Fine-Tuning Ye, Ziang, Zhenru Zhang, Yang Zhang, Jianxin Ma, Junyang Lin, and Fuli Feng ACL'25 (Findings)

pdf	Unveiling Language-Specific Features in Large Language Models via Sparse Autoencoders Deng, Boyi, Yu Wan, Yidan Zhang, Baosong Yang, and Fuli Feng ACL'25

pdf	HellaSwag-Pro: A Large-Scale Bilingual Benchmark for Evaluating the Robustness of LLMs in Commonsense Reasoning Li, Xiaoyuan, Moxin Li, Rui Men, Yichang Zhang, Keqin Bao, Wenjie Wang, Fuli Feng, Dayiheng Liu, and Junyang Lin ACL'25 (Findings)

pdf	Measuring What Makes You Unique: Difference-Aware User Modeling for Enhancing LLM Personalization Qiu, Yilun, Xiaoyan Zhao, Yang Zhang, Yimeng Bai, Wenjie Wang, Hong Cheng, Fuli Feng, and Tat-Seng Chua ACL'25 (Findings)

pdf	K-order Ranking Preference Optimization for Large Language Models Cai, Shihao, Chongming Gao, Yang Zhang, Wentao Shi, Jizhi Zhang, Keqin Bao, Qifan Wang, and Fuli Feng ACL'25 (Findings)

pdf	Improving Synthetic Image Detection Towards Generalization: An Image Transformation Perspective Li, Ouxiang, Jiayin Cai, Yanbin Hao, Xiaolong Jiang, Yao Hu, and Fuli Feng SIGKDD'25

pdf	Personalized Image Generation with Large Multimodal Models Xu, Yiyan, Wenjie Wang, Yang Zhang, Biao Tang, Peng Yan, Fuli Feng, and Xiangnan He WWW'25

pdf	CRAM: Credibility-Aware Attention Modification in LLMs for Combating Misinformation in RAG Deng, Boyi, Wenjie Wang, Fengbin Zhu, Qifan Wang, and Fuli Feng AAAI'25

pdf	Counterfactual Debating with Preset Stances for Hallucination Elimination of LLMs Fang, Yi, Moxin Li, Wenjie Wang, Hui Lin, and Fuli Feng COLING'25

pdf	Evaluating Mathematical Reasoning of Large Language Models: A Focus on Error Identification and Correction Li, Xiaoyuan, Wenjie Wang, Moxin Li, Junrong Guo, Yang Zhang, and Fuli Feng ACL'24 (Findings)

pdf	Think Twice Before Trusting: Self-Detection for Large Language Models through Comprehensive Answer Reflection Li, Moxin, Wenjie Wang, Fuli Feng, Fengbin Zhu, Qifan Wang, and Tat-Seng Chua EMNLP'24 (Findings)

pdf	Dual-Phase Accelerated Prompt Optimization Yang, Muchen, Moxin Li, Yongle Li, Zijun Chen, Chongming Gao, Junqi Zhang, Yangyang Li, and Fuli Feng EMNLP'24 (Findings)

pdf	Direct Multi-Turn Preference Optimization for Language Agents Shi, Wentao, Mengqi Yuan, Junkang Wu, Qifan Wang, and Fuli Feng EMNLP'24

pdf	Robust Prompt Optimization for Large Language Models Against Distribution Shifts Deng, Boyi, Wenjie Wang, Fuli Feng, Yang Deng, Qifan Wang and Xiangnan He EMNLP'23 (Findings)

pdf	Robust Instruction Optimization for Large Language Models with Distribution Shifts Li, Moxin, Wenjie Wang, Fuli Feng, Jizhi Zhang, and Tat-Seng Chua EMNLP'23 (Findings)

Recommendation:

pdf	Real-Time Personalization for LLM-based Recommendation with Customized In-Context Learning Bao, Keqin, Ming Yan, Yang Zhang, Jizhi Zhang, Wenjie Wang, Fuli Feng, and Xiangnan He ACL'25 (Findings)

pdf	Agentic Feedback Loop Modeling Improves Recommendation and User Simulation Cai, Shihao, Jizhi Zhang, Keqin Bao, Chongming Gao, Qifan Wang, Fuli Feng, and Xiangnan He SIGIR'25

pdf	Order-agnostic Identifier for Large Language Model-based Generative Recommendation Lin, Xinyu, Haihan Shi, Wenjie Wang, Fuli Feng, Qifan Wang, See-Kiong Ng, and Tat-Seng Chua SIGIR'25

pdf	Efficient Inference for Large Language Model-based Generative Recommendation Lin, Xinyu, Chaoqun Yang, Wenjie Wang, Yongqi Li, Cunxiao Du, Fuli Feng, See-Kiong Ng, and Tat-Seng Chua ICLR'25

pdf	Unconstrained Monotonic Calibration of Predictions in Deep Ranking Systems Bai, Yimeng, Shunyu Zhang, Yang Zhang, Hu Liu, Wentian Bao, Enyun Yu, Fuli Feng, and Wenwu Ou SIGIR'25

pdf	Large Language Models with Multi-faceted Relation Alignment for User Novel Interest Discovery Bi, Shuxian, Wenjie Wang, Moxin Li, Chongming Gao, and Fuli Feng PAKDD'25

pdf	Debias Can Be Unreliable: Mitigating Bias in Evaluating Debiasing Recommendation Wang, Chengbing, Wentao Shi, Jizhi Zhang, Wenjie Wang, Hang Pan, and Fuli Feng WWW'25 (Short)

pdf	Leveraging LLMs for Influence Path Planning in Proactive Recommendation Wang, Mingze, Shuxian Bi, Wenjie Wang, Chongming Gao, Yangyang Li, and Fuli Feng WWW'25 (Short)

pdf	Leveraging Memory Retrieval to Enhance LLM-based Generative Recommendation Wang, Chengbing, Yang Zhang, Fengbin Zhu, Jizhi Zhang, Tianhao Shi, and Fuli Feng WWW'25 (Short)

pdf	Envisioning Recommendations on an LLM-Based Agent Platform Zhang, Jizhi, Keqin Bao, Wenjie Wang, Yang Zhang, Wentao Shi, Wanhong Xu, Fuli Feng, and Tat-Seng Chua Communications of the ACM (2025)

pdf	Independent or Social Driven Decision? A Counterfactual Refinement Strategy for Graph-Based Social Recommendation Li, Dongyang, Jianshan Sun, Chongming Gao, Fuli Feng, and Kun Yuan ACM TOIS (2025)

pdf	A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems Bao, Keqin, Jizhi Zhang, Wenjie Wang, Yang Zhang, Zhengyi Yang, Yanchen Luo, Chong Chen, Fuli Feng, and Qi Tian ACM TORS (2025)

pdf	Text-like Encoding of Collaborative Information in Large Language Models for Recommendation Zhang, Yang, Keqin Bao, Ming Yan, Wenjie Wang, Fuli Feng, and Xiangnan He ACL'24

pdf	Decoding Matters: Addressing Amplification Bias and Homogeneity Issue in Recommendations for Large Language Models Bao, Keqin, Jizhi Zhang, Yang Zhang, Xinyue Huo, Chong Chen, and Fuli Feng EMNLP'24

pdf	Large Language Models Are Learnable Planners for Long-Term Recommendation Shi, Wentao, Xiangnan He, Yang Zhang, Chongming Gao, Xinyue Li, Jizhi Zhang, Qifan Wang, and Fuli Feng SIGIR'24

pdf	Diffusion Models for Generative Outfit Recommendation Xu, Yiyan, Wenjie Wang, Fuli Feng, Yunshan Ma, Jizhi Zhang, and Xiangnan He SIGIR'24

pdf	Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach Shi, Tianhao, Yang Zhang, Jizhi Zhang, Fuli Feng, and Xiangnan He SIGIR'24

pdf	Denoising Diffusion Recommender Model Zhao, Jujia, Wenjie Wang, Yiyan Xu, Teng Sun, Fuli Feng, and Tat-Seng Chua SIGIR'24

pdf	Data-efficient Fine-tuning for LLM-Based Recommendation Lin, Xinyu, Wenjie Wang, Yongqi Li, Shuo Yang, Fuli Feng, Yinwei Wei, and Tat-Seng Chua SIGIR'24

pdf	Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation Lin, Xinyu, Wenjie Wang, Yongqi Li, Fuli Feng, See-Kiong Ng, and Tat-Seng Chua SIGKDD'24

pdf	Learnable Item Tokenization for Generative Recommendation Wang, Wenjie, Honghui Bao, Xinyu Lin, Jizhi Zhang, Yongqi Li, Fuli Feng, See-Kiong Ng, and Tat-Seng Chua CIKM'24

pdf	Preliminary Study on Incremental Learning for Large Language Model-Based Recommender Systems Shi, Tianhao, Yang Zhang, Zhijian Xu, Chong Chen, Fuli Feng, Xiangnan He, and Qi Tian CIKM'24 (Short)

pdf	Debiased Recommendation with Noisy Feedback Li, Haoxuan, Chunyuan Zheng, Wenjie Wang, Hao Wang, Fuli Feng, and Xiao-Hua Zhou SIGKDD'24

pdf	GradCraft: Elevating Multi-Task Recommendations through Holistic Gradient Crafting Bai, Yimeng, Yang Zhang, Fuli Feng, Jing Lu, Xiaoxue Zang, Chenyi Lei, and Yang Song SIGKDD'24

pdf	Item-side Fairness of Large Language Model-Based Recommendation System Jiang, Meng, Keqin Bao, Jizhi Zhang, Wenjie Wang, Zhengyi Yang, Fuli Feng, and Xiangnan He WWW'24

pdf	Uplift Modeling for Target User Attacks on Recommender Systems Wang, Wenjie, Changsheng Wang, Fuli Feng, Wentao Shi, Daizong Ding, and Tat-Seng Chua WWW'24

pdf	Lower-left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation Shi, Wentao, Chenxu Wang, Fuli Feng, Yang Zhang, Wenjie Wang, Junkang Wu, and Xiangnan He WWW'24

pdf	Proactive Recommendation with Iterative Preference Guidance Bi, Shuxian, Wenjie Wang, Hang Pan, Fuli Feng, and Xiangnan He WWW'24 (Short)

pdf	Understanding and Counteracting Feature-Level Bias in Click-Through Rate Prediction Jin, Jinqiu, Sihao Ding, Wenjie Wang, and Fuli Feng WWW'24 (Short)

pdf	Temporally and Distributionally Robust Optimization for Cold-Start Recommendation Lin, Xinyu, Wenjie Wang, Jujia Zhao, Yongqi Li, Fuli Feng, and Tat-Seng Chua AAAI'24

pdf	Labelcraft: Empowering Short Video Recommendations with Automated Label Crafting Bai, Yimeng, Yang Zhang, Jing Lu, Jianxin Chang, Xiaoxue Zang, Yanan Niu, Yang Song, and Fuli Feng WSDM'24

pdf	Transferring Causal Mechanism over Meta-Representations for Target-Unknown Cross-Domain Recommendation Zhang, Shengyu, Qiaowei Miao, Ping Nie, Mengze Li, Zhengyu Chen, Fuli Feng, Kun Kuang, and Fei Wu ACM TOIS (2024)

pdf	Mitigating Hidden Confounding Effects for Causal Recommendation Zhu, Xinyuan, Yang Zhang, Xun Yang, Dingxian Wang, and Fuli Feng IEEE TKDE (2024)

pdf	Recommendation Unlearning via Influence Function Zhang, Yang, Zhiyu Hu, Yimeng Bai, Jiancan Wu, Qifan Wang, and Fuli Feng ACM TORS (2024)

pdf	Causal Intervention for Fairness in Multibehavior Recommendation Wang, Xi, Wenjie Wang, Fuli Feng, Wenge Rong, Chuantao Yin, and Zhang Xiong IEEE TCSS (2024)

pdf	Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach Jin, Jinqiu, Haoxuan Li, Fuli Feng, Sihao Ding, Peng Wu and Xiangnan He NeurIPS'23 (Poster)

pdf	Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach Li, Haoxuan, Kunhan Wu, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Fuli Feng, Xiangnan He, Zhi Geng and Peng Wu NeurIPS'23 (Poster)

pdf	Equivariant Learning for Out-of-Distribution Cold-Start Recommendation Wang, Wenjie, Xinyu Lin, Liuhui Wang, Fuli Feng, Yinwei Wei, and Tat-Seng Chua ACMMM'23

pdf	Leveraging Watch-time Feedback for Short-Video Recommendations: A Causal Labeling Framework Zhang, Yang, Yimeng Bai, Jianxin Chang, Xiaoxue Zang, Song Lu, Jing Lu, Fuli Feng, Yanan Niu and Yang Song CIKM'23 (Industry)

pdf	Can ChatGPT Make Fair Recommendation? A Fairness Evaluation Benchmark for Recommendation with Large Language Model Zhang, Jizhi, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng and Xiangnan He RecSys‘23 (Short)

pdf	LLM4Rec: Large Language Models for Recommendation via A Lightweight Tuning Framework Bao, Keqin, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng and Xiangnan He RecSys’23 (Short)

pdf	RecAD : Towards A Unified Library for Recommender Attack and Defense Wang, Changsheng, Jianbai Ye, Wenjie Wang, Chongming Gao, Fuli Feng and Xiangnan He RecSys‘23 (Reproducibility)

pdf	Diffusion Recommender Model Wang, Wenjie, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He, Tat-Seng Chua SIGIR’23 (Full)

pdf	Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation Zhang, Yang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He, Yongdong Zhang SIGIR’23 (Full)

pdf	Prediction then Correction: An Abductive Prediction Correction Method for Sequential Recommendation Huang, Yulong, Yang Zhang, Qifan Wang, Chenxu Wang, Fuli Feng SIGIR'23 (Short)

pdf	FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs Liu, Yang, Xiang Ao, Fuli Feng, Yunshan Ma, Kuan Li, Tat-Seng Chua, Qing He SIGKDD'23

pdf	On the Theories Behind Hard Negative Sampling for Recommendation Shi, Wentao, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao and Xiangnan He WWW'23

pdf	Anti-FakeU: Defending Shilling Attacks on Graph Neural Network based Recommender Model You, Xiaoyu, Chi Li, Daizong Ding, Mi Zhang, Fuli Feng, Xudong Pan, Min Yang WWW'23

pdf	Discriminative-Invariant Representation Learning for Unbiased Recommendation Pan, Hang, Jiawei Chen, Fuli Feng, Wentao Shi, Junkang Wu, and Xiangnan He IJCAI'23

pdf	A Causal View for Item-level Effect of Recommendation on User Preference Cai, Wei, Fuli Feng, Qifan Wang, Tian Yang, Zhenguang Liu and Congfu Xu WSDM'23

pdf	Unbiased Knowledge Distillation for Recommendation Chen, Gang, Jiawei Chen, Fuli Feng, Sheng Zhou and Xiangnan He WSDM'23

pdf	Personalized Latent Structure Learning for Recommendation Zhang, Shengyu, Fuli Feng, Kun Kuang, Wenqiao Zhang, Zhou Zhao, Hongxia Yang, Tat-Seng Chua and Fei Wu IEEE TPAMI (2023)

pdf	Causal Disentangled Recommendation Against User Preference Shifts Wang, Wenjie, Xinyu Lin, Liuhui Wang, Fuli Feng, Yunshan Ma, Tat-Seng Chua ACM TOIS (2023)

pdf	SLED: Structure Learning Based Denoising for Recommendation Zhang, Shengyu, Tan Jiang, Kun Kuang, Fuli Feng, Jin Yu, Jianxin Ma, Zhou Zhao, Jianke Zhu, Hongxia Yang, Tat-Seng Chua, and others ACM TOIS (2023)

pdf	Addressing Confounding Feature Issue for Causal Recommendation He, Xiangnan, Yang Zhang, Fuli Feng, Chonggang Song, Lingling Yi, Guohui Ling, and Yongdong Zhang ACM TOIS (2023)

pdf	Causal Distillation for Alleviating Performance Heterogeneity in Recommender Systems Zhang, Shengyu, Ziqi Jiang, Jiangchao Yao, Fuli Feng, Kun Kuang, Zhou Zhao, Shuo Li, Hongxia Yang, Tat-seng Chua, and Fei Wu IEEE TKDE (2023)

pdf	Rethinking Missing Data: Aleatoric Uncertainty-Aware Recommendation Wang, Chenxu, Fuli Feng, Yang Zhang, Qifan Wang, Xunhan Hu, and Xiangnan He IEEE TBD (2023)

pdf	Mitigating Spurious Correlations for Self-supervised Recommendation Lin, Xinyu, Yiyan Xu, Wenjie Wang, Yang Zhang, Fuli Feng Machine Intelligence Research (2023)

Others:

pdf	Pre-trained Behavioral Model for Malicious User Prediction on Social Platform Jiang, Meng, Wenjie Wang, Shaofeng Hu, Kaishen Ou, Zhenjing Zheng, and Fuli Feng AAAI'25

pdf	On the Maximal Local Disparity of Fairness-Aware Classifiers Jin, Jinqiu, Haoxuan Li, and Fuli Feng ICML'24

pdf	TAT-LLM: A Specialized Language Model for Discrete Reasoning over Financial Tabular and Textual Data Zhu, Fengbin, Ziyang Liu, Fuli Feng, Chao Wang, Moxin Li, and Tat-Seng Chua ACM ICAIF'24

pdf	Hogrn: Explainable Sparse Knowledge Graph Completion via High-Order Graph Reasoning Network Chen, Weijian, Yixin Cao, Fuli Feng, Xiangnan He, and Yongdong Zhang IEEE TKDE (2024)

pdf	Counterfactual Active Learning for Out-of-Distribution Generalization Deng, Xun, Wenjie Wang, Fuli Feng, Hanwang Zhang, Xiangnan He and Yong Liao ACL‘23

pdf	Hypothetical Training for Robust Machine Reading Comprehension of Tabular Context Li, Moxin, Wenjie Wang, Fuli Feng, Hanwang Zhang, Qifan Wang and Tat-Seng Chua ACL’23 (Findings)

pdf	MixPAVE: Mix-Prompt Tuning for Few-shot Product Attribute Value Extraction Yang, Li, Qifan Wang, Jingang Wang, Xiaojun Quan, Fuli Feng, Yu Chen, Madian Khabsa, Sinong Wang, Zenglin Xu and Dongfang Liu ACL‘23

pdf	MaSS: Model-agnostic, Semantic and Stealthy Data Poisoning Attack on Knowledge Graph Embedding You, Xiaoyu, Beina Sheng, Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Fuli Feng WWW'23

pdf	Lightmirm: Light Meta-Learned Invariant Risk Minimization for Trustworthy Loan Default Prediction Jiang, Meng, Yang Zhang, Yuan Gao, Yansong Wang, Fuli Feng, and Xiangnan He ICDE'23

pdf	Black-Box Adversarial Attack on Time Series Classification Ding, Daizong, Mi Zhang, Fuli Feng, Yuanmin Huang, Erling Jiang, and Min Yang AAAI'23

pdf	Video-audio Domain Generalization via Confounder Disentanglement Zhang, Shengyu, Xusheng Feng, Wenyan Fan, Wenjing Fang, Fuli Feng, Wei Ji, Shuo Li, Li Wang, Shanshan Zhao, Zhou Zhao, and others AAAI'23

pdf	Interactive Active Learning for Fairness with Partial Group Label Yang, Zeyu, Jizhi Zhang, Fuli Feng, Chongming Gao, Qifan Wang, and Xiangnan He AI Open (2023)

Professional Services

Program Committee Member of AAAI (2020) Program Committee Member of CIKM (2019) Program Committee Member of SIGIR (2019) Program Committee Member of ACMMM (2019) Program Committee Member of SIGIR (2018) Invited Reviewer for IEEE Transactions on Neural Networks and Learning Systems (TNNLS) Invited Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE) Invited Reviewer for Information Sciences Invited Reviewer for Multimedia Tools and Applications Invited Reviewer for World Wide Web Journal (WWWJ) Invited Reviewer for Multimedia Systems Journal (MMSJ) External Reviewer of WWW and WSDM in 2019. External Reviewer of AIRS, EMNLP, CIKM, ACMMM, ACL, IJCAI, KDD, AAAI, and WSDM in 2018. External Reviewer of AIRS, EMNLP, CIKM, ACMMM, ACL, IJCAI, KDD, AAAI, and WSDM in 2017.

Education

National University of Singapore (NUS) Ph.D. in Computer Science                   August 2015 - August 2019, Singapore Advisor: Prof. Tat-Seng Chua Mentors: Prof. Xiangnan He and Prof. Liqiang Nie

Beihang University (BUAA) Bachelor in Computer Science and Engineering      September 2011 - June 2015, Beijing Advisor: Prof. Zhoujun Li

Experiences

Professor, University of Science and Technology of China, February 2022 - Present

Postdoc Research Fellow, National University of Singapore, June 2019 - January 2022 Advisior: Prof. Tat-Seng Chua (NExT++: NUS-Tsinghua-Southampton Extreme Search Center)

Selected Awards

Dean's Graduate Research Excellence Award,    2018    - School of Computing, National University of Singapore

Best Poster Award,    2018    - The Web Conference (WWW)

Research Achievement Award,    2017    - School of Computing, National University of Singapore

Outstanding Undergraduate Award,   2014    - China Computer Federation (CCF)

1st Prize Award,   2014    - ASC World Student Supercomputer Challenge

Application Innovation Award,   2014    - ASC World Student Supercomputer Challenge

Useful Links

Lab for Data Science

Stanford CS25

智荐阁（公众号同名）

Last update: 2025.06.23. Webpage template borrows from Prof. Xiangnan He.