News
Mar 2023
One full paper is accepted by SIGIR2023, about diffusion recommender models.
Feb 2023
One full paper is accepted by TOIS, about causal OOD recommendation.
Sep 2022
Awarded Google PhD Fellowship 2022! Thanks all!
Mar 2022
Two full papers are accepted by SIGIR2022, about Controllable Filter Bubbles and Debiasing Recommendation.
Feb 2022
One full paper is accepted by WWW2022, about Causal OOD Recommendation.
May 2021
One full paper is accepted by KDD2021, about Causal Recommendation.
Apr 2021
One full paper is accepted by SIGIR2021, about Causal Recommendation.
Oct 2020
One full paper is accepted by WSDM2021, about Denoising Recommendation.
05 Sep 2020
I am invited to be a Program Committee memeber in AAAI 2021.
Aug 2020
One full paper is accepted by TOMM, about Food Recommendation.
Aug 2020
One full paper is accepted by ACMMM 2020, about Micro-video Recommendation.
30 Apr 2020
I am invited to be a Technical Program Committee memeber in ACM Multimedia 2020.
21 Oct 2019
One full paper and one demo paper are accepted by ACMMM 2019, about multimodal dialog system.
25 July 2019
One full paper is accepted by SIGIR 2019, about multimodal dialog system.
6 July 2018
One full paper is accepted by SIGIR 2018, about open-domain dialog system.
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Wenjie Wang
Postdoctoral Research Fellow
NExT++
Computing 1, Computing Drive, Singapore 117417
Email: wenjiewang96 AT gmail.com
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I am a research fellow, working with Prof. Tat-Seng Chua and Prof. See-Kiong Ng in National University of Singapore. I obtained my PhD from NUS in 2023, also supervised by Prof. Chua. Prior to that, I received my B.Eng. degree from Shandong University (Elite Class) in 2019, supervised by Prof. Liqiang Nie . My research interests include information retrieval, causal recommendation, and multi-media analytics.
PS: I am looking for highly motivated PhD/master/undergraduate students to collaborate on various interesting research topics, including generative models (e.g., LLMs) for recommendation, causal recommendation, LLM for search, and personalized agents etc. If you have interest, please feel free to send your CV to wenjiewang96@gmail.com.
Education
| National University of Singapore (NUS) Ph.D. in Computer Science, 2019 - 2023, Singapore Advisor: Prof. Tat-Seng Chua Mentors: Prof. Fuli Feng and Prof. Xiangnan He |
| Shandong University (SDU) Bachelor in Computer Science and Engineering (Elite Class), 2015 - 2019, Qingdao Advisor: Prof. Liqiang Nie |
Experiences
| Intern, CoAI, Tsinghua University, June 2017 - August 2017 Advisior: Prof. Minlie Huang |
Tutorials, Surveys, and Workshops
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A survey of generative search and recommendation in the era of large language models
Yongqi Li, Xinyu Lin, Wenjie Wang, Fuli Feng, Liang Pang, Wenjie Li, Liqiang Nie, Xiangnan He, Tat-Seng Chua arXiv |
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Large Language Models for Recommendation: Progresses and Future Directions
Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He SIGIR 2024, WWW 2024, SIGIR-AP 2023 Slides |
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The 2nd Workshop on Recommendation with Generative Models
Wenjie Wang, Yang Zhang, Xinyu Lin, Fuli Feng, Yong Liu, Weiwen Liu, Xiangyu Zhao, Wayne Xin Zhao, Yang Song, Xiangnan He WWW 2024 Website |
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The 1st Workshop on Recommendation with Generative Models
Wenjie Wang, Yong Liu, Yang Zhang, Weiwen Liu, Fuli Feng, Xiangnan He, Aixin Sun CIKM 2023 Website |
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Causal inference in recommender systems: A survey and future directions
Chen Gao, Yu Zheng, Wenjie Wang, Fuli Feng, Xiangnan He, Yong Li TOIS |
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Causal Recommendation: Progresses and Future Directions
Wenjie Wang, Yang Zhang, Haoxuan Li, Peng Wu, Fuli Feng, Xiangnan He SIGIR 2023, WWW 2022 Slides |
Publications Google Scholar
*Corresponding author In the Year of 2024: |
Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation
Xinyu Lin, Wenjie Wang*, Yongqi Li, Fuli Feng*, See-Kiong Ng, Tat-Seng Chua KDD 2024 |
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Debiased Recommendation with Noisy Feedback
Haoxuan Li, Chunyuan Zheng, Wenjie Wang, Hao Wang, Fuli Feng, Xiao-Hua Zhou KDD 2024 |
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Learnable Tokenizer for LLM-based Generative Recommendation
Wenjie Wang, Honghui Bao, Xinyu Lin, Jizhi Zhang, Yongqi Li, Fuli Feng, See-Kiong Ng, Tat-Seng Chua CIKM 2024 |
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Generative Recommendation: Towards Next-generation Recommender Paradigm
Wenjie Wang, Xinyu Lin, Fuli Feng, Xiangnan He, Tat-Seng Chua |
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Data-efficient Fine-tuning for LLM-based Recommendation
Xinyu Lin, Wenjie Wang*, Yongqi Li, Shuo Yang, Fuli Feng*, Yinwei Wei, Tat-Seng Chua SIGIR 2024 |
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A Taxation Perspective for Fair Re-ranking
Chen Xu, Xiaopeng Ye, Wenjie Wang*, Liang Pang, Jun Xu*, Tat-Seng Chua SIGIR 2024 (Best Paper Honorable Mention Award) |
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Diffusion Models for Generative Outfit Recommendation
Yiyan Xu, Wenjie Wang*, Fuli Feng*, Yunshan Ma, Jizhi Zhang, Xiangnan He SIGIR 2024 |
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Treatment Effect Estimation for User Interest Exploration on Recommender Systems
Jiaju Chen, Wenjie Wang*, Chongming Gao, Peng Wu, Jianxiong Wei, Qingsong Hua SIGIR 2024 |
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Denoising diffusion recommender model
Jujia Zhao, Wenjie Wang*, Yiyan Xu, Teng Sun, Fuli Feng, Tat-Seng Chua SIGIR 2024 |
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I3: Intent-Introspective Retrieval Conditioned on Instructions
Kaihang Pan, Juncheng Li, Wenjie Wang, Hao Fei, Hongye Song, Wei Ji, Jun Lin, Xiaozhong Liu, Tat-Seng Chua, Siliang Tang SIGIR 2024 |
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Generative cross-modal retrieval: Memorizing images in multimodal language models for retrieval and beyond
Yongqi Li, Wenjie Wang*, Leigang Qu, Liqiang Nie, Wenjie Li, Tat-Seng Chua ACL 2024 |
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Text-like Encoding of Collaborative Information in Large Language Models for Recommendation
Yang Zhang, Keqin Bao, Ming Yan, Wenjie Wang, Fuli Feng, Xiangnan He ACL 2024 |
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Evaluating Mathematical Reasoning of Large Language Models: A Focus on Error Identification and Correction
Xiaoyuan Li, Wenjie Wang*, Moxin Li, Junrong Guo, Yang Zhang, Fuli Feng ACL Findings 2024 |
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Distillation Enhanced Generative Retrieval
Yongqi Li, Zhen Zhang, Wenjie Wang*, Liqiang Nie, Wenjie Li, Tat-Seng Chua ACL Findings 2024 |
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Discriminative probing and tuning for text-to-image generation
Leigang Qu, Wenjie Wang*, Yongqi Li, Hanwang Zhang, Liqiang Nie, Tat-Seng Chua CVPR 2024 |
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Uplift Modeling for Target User Attacks on Recommender Systems
Wenjie Wang, Changsheng Wang, Fuli Feng*, Wentao Shi, Daizong Ding, Tat-Seng Chua WWW 2024 |
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Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation
Wentao Shi, Chenxu Wang, Fuli Feng, Yang Zhang, Wenjie Wang, Junkang Wu, Xiangnan He WWW 2024 |
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Item-side Fairness of Large Language Model-based Recommendation System
Meng Jiang, Keqin Bao, Jizhi Zhang, Wenjie Wang, Zhengyi Yang, Fuli Feng and Xiangnan He WWW 2024 Web4Good |
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Proactive Recommendation with Iterative Preference Guidance
Shuxian Bi, Wenjie Wang*, Hang Pan, Fuli Feng, Xiangnan He WWW 2024 (Short) |
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Temporally and Distributionally Robust Optimization for Cold-start Recommendation
Xinyu Lin, Wenjie Wang*, Jujia Zhao, Yongqi Li, Fuli Feng, Tat-Seng Chua AAAI 2024 |
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GOODAT: Towards Test-time Graph Out-of-Distribution Detection
Luzhi Wang, Dongxiao He, He Zhang, Yixin Liu, Wenjie Wang, Shirui Pan, Di Jin, Tat-Seng Chua AAAI 2024 |
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Robust Prompt Optimization for Large Language Models Against Distribution Shifts
Moxin Li, Wenjie Wang*, Fuli Feng, Yixin Cao, Jizhi Zhang and Tat-Seng Chua EMNLP (Main) |
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Attack Prompt Generation for Red Teaming and Defending Large Language Model
Boyi Deng, Wenjie Wang*, Fuli Feng, Yang Deng, Qifan Wang and Xiangnan He EMNLP (Finding) |
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Popularity-aware Distributionally Robust Optimization for Recommendation System
Jujia Zhao, Wenjie Wang*, Xinyu Lin, Leigang Qu, Jizhi Zhang, Tat-Seng Chua CIKM 2023 |
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Can ChatGPT Make Fair Recommendation? A Fairness Evaluation Benchmark for Recommendation with Large Language Model
Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng and Xiangnan He RecSys 2023 (Short) |
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Tallrec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation
Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng and Xiangnan He RecSys 2023 (Short) |
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RecAD : Towards A Unified Library for Recommender Attack and Defense
Changsheng Wang, Jianbai Ye, Wenjie Wang*, Chongming Gao, Fuli Feng and Xiangnan He RecSys 2023 (Reproducibility) |
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Equivariant Learning for Out-of-Distribution Cold-start Recommendation
Wenjie Wang, Xinyu Lin, Liuhui Wang, Fuli Feng, Yinwei Wei, Tat-Seng Chua ACMMM 2023 (Oral) |
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General Debiasing for Multimodal Sentiment Analysis
Teng Sun, Juntong Ni, Wenjie Wang*, Liqiang Jing, Yinwei Wei, Liqiang Nie ACMMM 2023 (Poster) |
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Diffusion Recommender Model
Wenjie Wang, Yiyan Xu, Fuli Feng*, Xinyu Lin, Xiangnan He, Tat-Seng Chua SIGIR 2023 (Full) |
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Learnable Pillar-based Re-ranking for Image-Text Retrieval
Leigang Qu, Meng Liu, Wenjie Wang*, Zhedong Zheng, Liqiang Nie, Tat-Seng Chua SIGIR 2023 (Full) |
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Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation
Yang Zhang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He, Yongdong Zhang SIGIR 2023 (Full) |
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Causal Disentangled Recommendation Against User Preference Shifts
Wenjie Wang, Xinyu Lin, Liuhui Wang, Fuli Feng, Yunshan Ma, Tat-Seng Chua TOIS 2023 (Full) |
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Dynamic Multimodal Fusion via Meta-Learning Towards Micro-Video Recommendation
Han Liu, Yinwei Wei, Fan Liu, Wenjie Wang, Liqiang Nie, Tat-Seng Chua TOIS 2023 (Full) |
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Counterfactual Active Learning for Out-of-Distribution Generalization
Xun Deng, Wenjie Wang*, Fuli Feng, Hanwang Zhang, Xiangnan He, Yong Liao ACL 2023 (Full) |
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Hypothetical Training for Robust Machine Reading Comprehension of Tabular Context
Moxin Li, Wenjie Wang*, Fuli Feng, Hanwang Zhang, Qifan Wang, Tat-Seng Chua ACL findings 2023 (Full) |
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Mitigating Spurious Correlations for Self-supervised Recommendation
Xinyu Lin, Yiyan Xu, Wenjie Wang*, Yang Zhang, Fuli Feng MIR 2023 (Full) |
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Causal Representation Learning for Out-of-Distribution Recommendation
Wenjie Wang, Xinyu Lin, Fuli Feng*, Xiangnan He, Min Lin, Tat-Seng Chua WWW 2022 (Full, Accept rate: 17.7%) Codes |
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User-controllable Recommendation Against Filter Bubbles
Wenjie Wang, Fuli Feng*, Liqiang Nie and Tat-Seng Chua SIGIR 2022 (Full, Accept rate: 20%) |
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Interpolative Distillation for Unifying Biased and Debiased Recommendation
Sihao Ding, Fuli Feng*, Xiangnan He, Jinqiu Jin, Wenjie Wang, Yong Liao and Yongdong Zhang SIGIR 2022 (Full, Accept rate: 20%) |
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Dynamic Hypergraph Convolutional Network
Nan Yin, Fuli Feng, Zhigang Luo, Xiang Zhang, Wenjie Wang, Xiao Luo, Chong Chen and Xian-Sheng Hua ICDE 2022 (Full) |
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Counterfactual Reasoning for Out-of-distribution Multimodal Sentiment Analysis
Teng Sun, Wenjie Wang*, Liqaing Jing, Yiran Cui, Xuemeng Song and Liqiang Nie* ACMMM 2022 (Oral) |
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Deconfounded Recommendation for Alleviating Bias Amplification
Wenjie Wang, Fuli Feng*, Xiangnan He, Xiang Wang, Tat-Seng Chua KDD 2021 (Full, Accept rate: 15.4%) Codes |
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Clicks can be Cheating: Counterfactual Recommendation for Mitigating Clickbait Issue
Wenjie Wang, Fuli Feng*, Xiangnan He, Hanwang Zhang, Tat-Seng Chua SIGIR 2021 (Full, Accept rate: 21%) Codes |
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Denoising Implicit Feedback for Recommendation
Wenjie Wang, Fuli Feng*, Xiangnan He, Liqiang Nie, Tat-Seng Chua WSDM 2021 (Full, Accept rate: 18.6%) Codes |
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Conversational Image Search
Liqiang Nie, Fangkai Jiao, Wenjie Wang, Yinglong Wang, Qi Tian TIP 2021 (Full) |
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What Aspect Do You Like: Multi-scale Time-aware User Interest Modeling for Micro-video Recommendation
Hao Jiang, Wenjie Wang*, Yinwei Wei, Zan Gao, Liqiang Nie* ACMMM 2020 (Full) |
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Market2Dish: Health-aware Food Recommendation System
Wenjie Wang, Ling-yu Duan, Hao Jiang, Xuemeng Song, Liqiang Nie* TOMM (Full) Codes |
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User Atention-guided Multimodal Dialog Systems
Chen Cui, Wenjie Wang, Xuemeng Song, Minlie Huang, Xin-Shun Xu, Liqiang Nie* SIGIR 2019 (Full) Codes |
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Multimodal Dialog System: Generating Responses via Adaptive Decoders
Liqiang Nie*, Wenjie Wang, Richang Hong, Meng Wang, Qi Tian ACMMM 2019 (Full) Codes (Best Paper Final List) |
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Market2Dish: A Health-aware Food Recommendation System
Hao Jiang, Wenjie Wang, Meng Liu, Liqiang Nie, Ling-Yu Duan, Changsheng Xu ACMMM 2019 (Demo) Codes |
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Chat more: Deepening and widening the chatting topic via a deep model
Wenjie Wang, Minlie Huang, Xin-Shun Xu, Fumin Shen, Liqiang Nie* SIGIR 2018 (Full) Codes |
Honors
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Best Paper Honorable Mention Award at SIGIR 2024 |
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Best Presentation Award at Singapore ACM SIGKDD Symposium 2023 |
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Google PhD Fellowship, 2022 |
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Dean’s Graduate Research Excellence Award, Aug 2022
- School of Computing, National University of Singapore |
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Research Achievement Award, Aug 2021
- School of Computing, National University of Singapore |
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Best Paper Final List at ACMMM 2019 |
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President Scholarship, Dec 2018
- Highest honor in Shandong University |
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National Scholarship, Dec 2017
- Shandong University, China |
Invited Talks
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Causal Inference for Trustworthy Recommender Systems
- ACM RecSys Workshop Keynote, CONSEQUENCES, Singapore, Sep 2023 |
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Large Language Models for Recommendation: Progresses and Prospects
- MLNLP 2023, Sep 2023; MIR forum Aug 2023 |
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Causal Recommender System
- Beijing Super Cloud Computing Center & Shandong University Taishan College, Apr, 2023 |
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Denoising Implicit Feedback for Recommendation
- WSDM 2021, Online Conference, Mar, 2021 |
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Multimodal Dialog System: Generating Responses via Adaptive Decoders
- ACMMM 2019 Best Paper Session, Nice, France, Oct, 2019 |
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Chat more: Deepening and widening the chatting topic via a deep model
- SIGIR 2018, Ann Arbor MI, USA, July, 2018 |
Professional Services
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Web Chair for SIGIR 2024 Guest Editor for TOIS Special Issue on Pre-trained Models for Search and Recommendation Invited Reviewer for TOIS, TPAMI, TMM, TCSVT, TNNLS, TORS, TSP, Multimedia Systems Program Committee Member of AAAI, WSDM, WWW, KDD, ACMMM, RecSys, IJCAI, SIGIR in 2024 Program Committee Member of AAAI, WSDM, WWW, KDD, ACMMM, RecSys, IJCAI, SIGIR in 2023 Program Committee Member of AAAI, WSDM, ACMMM, KDD in 2022 Program Committee Member of AAAI, ACMMM, ECML/PKDD in 2021 Program Committee Member of ACMMM in 2020 |
Teaching Assistants
| CS5228 Knowledge Discovery and Data Mining 2019/2020 semester 2 |
| CS2103/T: Software Engineering 2020/2021 Semester 1 |
| CS5260 Neural Networks and Deep Learning II 2020/2021 Semester 2 |
Last update: Jul, 2024. Webpage template borrows from Prof. Xiangnan He.