冯福利

地址: 中科大高新校区，信智大楼B404

主要研究兴趣：

My research interests include information retrieval, data mining, and multi-media analytics, particularly in machine learning techniques and applications such as causal inference, graph neural networks, adversarial learning, multi-source learning, recommender systems, FinTech, and text mining. Moreover, I have served as the PC member for top-tier conferences including SIGIR, WWW, SIGKDD, NeurIPS, ICLR, ICML, ACL, and ACMMM, and the invited reviewer for prestigious journals such as TOIS, TKDE, TPAMI, TNNLS, and TMM.

招生信息：

1. Hiring tenure-track faculties and postdocs in NLP/IR/DM. Requirements:

- With PhD degree (or graduate soon)

- At least three first-author papers on tier-1 conferences

2. Hiring PhD students from USTC and masters. Requirements:

- Strong code ability (C/C++ or Python)

- English (CET-6 score 500+, or equal levels)

- Determination to do high-quality research.

3. Hiring master students and undergraduate interns. Requirements:

- Strong code ability (C/C++ or Python)

- Determination to do high-quality research.

- Experience in high-level competitions (e.g., ACM-ICPC and KDD-Cup) will be considered.

研究经历：

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

August 2019 - December 2021, Postdoc Research Fellow, National University of Singapore

三年内主要论著（2020至今）：

[01] Sihao Ding, Fuli Feng, Xiangnan He, Yong Liao, Jun Shi and Yongdong Zhang. Causal Incremental Graph Convolution for Recommender System Retraining. IEEE TNNLS 2022

[02] Moxin Li, Fuli Feng, Hanwang Zhang, Xiangnan He, Fengbin Zhu and Tat-Seng Chua. Learning to Imagine: Integrating Counterfactual Thinking in Neural Discrete Reasoning.. ACL 2022 (Full)

[03] Wenjie Wang, Xinyu Lin, Fuli Feng, Xiangnan He, Min Lin and Tat-Seng Chua. Causal Representation Learning for Out-of-Distribution Recommendation.. WWW 2022 (Full)

[04] Yu Wang, Xin Xin, Zaiqiao Meng, Joemon Jose, Fuli Feng and Xiangnan He. Learning Robust Recommenders through Cross-Model.. WWW 2022 (Full)

[05] Qifan Wang, Yi Fang, Anirudh Ravula, Fuli Feng, Xiaojun Quan and Dongfang Liu. WebFormer: The Web-page Transformer for Structure Information Extraction. WWW 2022 (Full)

[06] Re4: Learning to Re-contrast, Re-attend, Re-construct for Multi-interest Recommendation. Shengyu Zhang, Lingxiao Yang, Dong Yao, Yujie Lu, Fuli Feng, Zhou Zhao, Tat-Seng Chua and Fei Wu. WWW 2022 (Full)

[07] Daizong Ding, Mi Zhang, Yuanmin Huang, Xudong Pan, Fuli Feng, Erling Jiang and Min Yang. Towards Backdoor Attack on Deep Learning based Time Series Classification. ICDE 2022 (Full)

[08] Teng Sun, Chun Wang, Xuemeng Song, Fuli Feng and Liqiang Nie. Response Generation by Jointly Modeling Personalized Linguistic Styles and Emotions. ACM TOMM 2022

[09] Wenjie Wang, Fuli Feng, Xiangnan He, Xiang Wang and Tat-Seng Chua. Deconfounded recommendation for alleviating bias amplification. SIGKDD 2021 (Full)

[10] Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi and Xiangnan He. Model-agnostic counterfactual reasoning for eliminating popularity bias in recommender system. SIGKDD 2021 (Full)

[11] Yang Zhang, Fuli Feng, Xiangnan He, Tianxin Wei, Chonggang Song, Guohui Ling and Yongdong Zhang. Causal intervention for leveraging popularity bias in recommendation. SIGIR 2021 (Full) Best paper award honourable mention

[12] Xun Yang, Fuli Feng, Wei Ji, Meng Wang and Tat-Seng Chua. Deconfounded video moment retrieval with causal intervention. SIGIR 2021 (Full)

[13] Fuli Feng, Weiran Huang, Xiangnan He, Xin Xin, Qifan Wang and Tat-Seng Chua. Should graph convolution trust neighbors? a simple causal inference method. SIGIR 2021 (Full)

[14] Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian and Xing Xie. Self-supervised Graph Learning for Recommendation. SIGIR 2021 (Full)

[15] Fuli Feng, Moxin Li, Cheng Luo, Ritchie Ng, Tat-Seng Chua. Hybrid learning to rank for financial event ranking. SIGIR 2021 (Full)

[16] Fuli Feng, Jizhi Zhang, Xiangnan He, Hanwang Zhang and Tat-Seng Chua. Empowering Language Understanding with Counterfactual Reasoning. ACL 2021 (Findings)

[17] Fengbin Zhu, Wenqiang Lei, Youcheng Huang, Chao Wang, Shuo Zhang, Jiancheng Lv, Fuli Feng and Tat-Seng Chua. TAT-QA: A question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance. ACL 2021 (Full)

[18] Chen Qian, Fuli Feng, Lijie Wen, Chunping Ma and Pengjun Xie. Counterfactual Inference for Text Classification Debiasing. ACL 2021 (Full)

[19] Hande Dong, Jiawei Chen, Fuli Feng, Xiangnan He, Shuxian Bi, Zhaolin Ding and Peng Cui. On the Equivalence of Decoupled Graph Convolution Network and Label Propagation. WWW 2021 (Full)

[20] Chen Qian, Fuli Feng, Lijie Wen and Tat-Seng Chua. Conceptualized and Contextualized Gaussian Embedding. AAAI 2021 (Full)

[21] Wenjie Wang, Fuli Feng, Xiangnan He, Liqiang Nie and Tat-Seng Chua. Denoising Implicit Feedback for Recommendation. WSDM 2021 (Full)

[22] Xiaoyu You, Mi Zhang, Daizong Ding, Fuli Feng and Yuanmin Huang. Learning to Learn the Future: Modeling Concept Drifts in Time Series Prediction. CIKM 2021 (Full)

[23] Fuli Feng, Xiangnan He, Hanwang Zhang and Tat-Seng Chua. Cross-GCN: Enhancing Graph Convolutional Network with k-Order Feature Interactions. TKDE 2021

[24] Weijian Chen, Fuli Feng, Qifan Wang, Xiangnan He, Chonggang Song, Guohui Ling and Yongdong Zhang. CatGCN: Graph Convolutional Networks with Categorical Node Features. TKDE 2021

[25] Chen Gao, Yong Li, Fuli Feng, Xiangning Chen, Kai Zhao, Xiangnan He and Depeng Jin. Cross-domain Recommendation with Bridge-Item Embeddings. TKDD 2021

[26] Xin Yang, Xuemeng Song, Fuli Feng, Haokun Wen, Ling-Yu Duan and Liqiang Nie. Attribute-wise Explainable Fashion Compatibility Modeling. ACM TOMM 2021

[27] Weili Guan, Zhaozheng Chen, Fuli Feng, Weifeng Liu and Liqiang Nie. Urban Perception: Sensing Cities via a Deep Interactive Multi-task Learning Framework. ACM TOMM 2021

[28] Shunyu Jiang, Fuli Feng, Weijian Chen, Xiang Li and Xiangnan He. Structure-enhanced Meta-learning for Few-shot Graph Classification. AI Open 2021 (Full)

[29] Lei Meng, Fuli Feng, Xiangnan He, Xiaoyan Gao and Tat-Seng Chua. Heterogeneous Fusion of Semantic and Collaborative Information for Visually-Aware Food Recommendation. ACMMM 2020 (Full)

[30] Yang Zhang, Fuli Feng, Chenxu Wang, Xiangnan He, Meng Wang, Yan Li and Yongdong Zhang. How to Retrain Recommender System? A Sequential Meta-Learning Approach. SIGIR 2020 (Full)

[31] Chen Qian, Fuli Feng, Lijie Wen, Li Lin, & Tat-Seng Chua. Enhancing Text Classification via Discovering Additional Semantic Clues from Logograms. SIGIR 2020 (Full)

[32] Hongmin Zhu, Fuli Feng, Xiangnan He, Xiang Wang, Yan Li, Kai Zheng and Yongdong Zhang. Bilinear Graph Neural Network with Neighbor Interactions. IJCAI 2020 (Full)

[33] Chen Qian, Fuli Feng, Lijie Wen, Zhenpeng Chen, Li Lin, Yanan Zheng and Tat-Seng Chua. Solving Sequential Text Classification as Board-Game Playing. AAAI 2020 (Full)

[34] Liqiang Nie, Yongqi Li, Fuli Feng, Xuemeng Song, Meng Wang and Tat-Seng Chua. Large-Scale Question Tagging via Joint Question-Topic Embedding Learning. ACM TOIS 2020

[35] Tianxin Wei, Ziwei Wu, Ruirui Li, Ziniu Hu, Fuli Feng, Xiangnan He; Yizhou Sun and Wei Wang. Fast Adaptation for Cold-Start Collaborative Filtering with Meta-Learning. ICDM 2020 (Full)