News


15 Jan. 2022
One full paper is accepted by WWW'22, on Hypergraph-based Personalized Search.

29 Dec. 2021
We release a new version of the survey on recommendation debiasing, with supplementing causal explanations of biases and the latest debiasing technologies.

8 Aug. 2021
One full paper is accepted by CIKM'21, on disentangled knowledge graph representation learning.

27 July. 2021
One full paper is accepted by ICCV'21, on GCN-based knowledge distillation.

27 July. 2021
One full paper is accepted by TKDE, on sampling for recommendation.

12 June. 2021
Our tutorial on Bias and debias in recommendation is also accepted by Recsys'21.

18 May 2021
One full paper is accepted by KDD'21, on causal inference for recommendation debiasing.

15 April 2021
One full paper is accepted by SIGIR'21, on universal debiasing framework for recommendation .

7 Feb. 2021
One full paper is accepted by TOIS'21, on Sampling for recommendation .

15 Jan. 2021
One full paper is accepted by WWW'21, on Equivalence of GCN and label propagation .

15 Dec. 2020
One tutorial is accepted by WWW'21, on Bias and debias in recommendation.

11 Nov. 2019
Two full papers are accepted by AAAI, on Unbiased recommendation and Graph embedding.

Jiawei Chen 

Research fellow

Lab of Data Science
School of Information Science and Technology
University of Science and Technology of China

443 Huangshan Road, Hefei, China 230027

Email: cjwustc AT ustc.edu.cn

I am a Posdoc Research Fellow in LDS (Lab of Data Science), School of Information Science and Technology, University of Science and Technology of China. I have several publications appeared in several top conferences such as AAAI, WWW, ICDM, ICDE and CIKM. My research interests include information retrieval, data mining and machine learning, particularly in recommender systems, sampling, graph neural network. Moreover, I have served as the PC member for top-tier conferences including SIGIR, ACMMM, PKDD-ECML and the invited reviewer for prestigious journals such as TNNLS, TKDE, TOIS.

Notes: We recently release a new version of the survey on biases in recommender system:
- Bias and Debias in Recommender System: A Survey and Future Directions
- You may be interested in this emerging topic!

Tutorial


pdf
Bias Issues and Solutions in Recommender System
Jiawei Chen, Xiang Wang, Fuli Feng, Xiangnan He
WWW'21, RecSys'21    Slide

Selected Publications



pdf
Bias and Debias in Recommender System: A Survey and Future Directions
Jiawei Chen, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang, Xiangnan He
arXiv:2010.03240   

pdf
Interactive Hypergraph Neural Network for Personalized Product Search
Dian Cheng, Jiawei Chen*, Wenjun Peng, Wenqin Ye, Fuyu Lv, Tao Zhuang, Xiaoyi Zeng & Xiangnan He
WWW'2022 (Full, Accept rate: 17.7%), *Corresponding author  

pdf
DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network
Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen* Wenqiang Lei, Fuzheng Zhang, Wei Wu, Xiangnan He
CIKM'2021 (Full, Accept rate: 21.7%), *Corresponding author  

pdf
SamWalker++: Recommendation with Informative Sampling Strategy
Can Wang, Jiawei Chen*, Sheng Zhou, Qihao Shi, Yan Feng and Chun Chen
TKDE, *Corresponding author  

pdf
Distilling Holistic Knowledge with Graph Neural Networks
Sheng Zhou, Yuchen Wang, Defang Chen, Jiawei Chen, Xin Wang, Can Wang, Jiajun Bu
ICCV'21 (Full, Accept rate: 25.9%)   

pdf
Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System
Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi & Xiangnan He
KDD'2021 (Full, Accept rate: 15.4%)   

pdf
AutoDebias: Learning to Debias for Recommendation
Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, Keping Yang
SIGIR'2021 (Full, Accept rate: 21%)   

pdf
CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation
Jiawei Chen, Chengquan Jiang, Can Wang, Sheng Zhou, Yan Feng, Chun Chen, Martin Ester, Xiangnan He
TOIS'2021   

pdf
On the Equivalence of Decoupled Graph Convolution Network and Label Propagation
Hande Dong,Jiawei Chen*, Fuli Feng, Xiangnan He, Shuxian Bi, Zhaolin Ding, Peng Cui
WWW'2021 (Full, Oral, Accept rate: 20.6% ), *Corresponding author   

pdf
Fast Adaptively Weighted Matrix Factorization for Recommendation with Implicit Feedback
Jiawei Chen, Can Wang, Sheng Zhou, Qihao Shi, Jingbang Chen, Yan Feng, Chun Chen
AAAI 2020 (Full, Oral, Accept rate: 20.6%)   

pdf
DGE: Deep Generative Network Embedding Based on Commonality and Individuality
Sheng Zhou, Xin Wang, Jiajun Bu, Martin Ester, Pinggang Yu, Jiawei Chen , Qihao Shi, Can Wang
AAAI 2020 (Full, Poster, Accept rate: 20.6%)   

pdf
Samwalker: Social recommendation with informative sampling strategy
Jiawei Chen, Can Wang, Sheng Zhou, Qihao Shi, Yan Feng, Chun Chen
WWW 2019 (Full, Oral, Accept rate: 18%)   

pdf
Adaptive Influence Blocking: Minimizing the Negative Spread by Observation-Based Policies
Qihao Shi, Can Wang, Deshi Ye, Jiawei Chen, Yan Feng, Chun Chen
ICDE 2019 (Full, Oral)   

pdf
Social recommendation with missing not at random data
Jiawei Chen, Can Wang, Martin Ester, Qihao Shi, Yan Feng, Chun Chen
ICDM 2018 (Full, Oral, Accept rate: 8.86%)   

pdf
Modeling Users' Exposure with Social Knowledge Influence and Consumption Influence for Recommendation
Jiawei Chen, Yan Feng, Martin Ester, Sheng Zhou, Chun Chen, Can Wang
CIKM 2018 (Full, Oral, Accept rate: 17%)   

Professional Services

PC/SPC Member of Conferences:
Senior Program Committee Member of IJCAI (2021)
Program Committee Member of WWW (2021)
Program Committee Member of AAAI (2021)
Program Committee Member of SIGIR (2020)
Program Committee Member of ACMMM (2020)
Program Committee Member of ECML-PKDD (2020)
Invited Reviewer for IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
Invited Reviewer for IEEE Transactions on Information system (TOIS)
Invited Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE)
Invited Reviewer for Neurocomputing

Experiences

Postdoc Research Fellow, University of Science and Technology of China, July 2020 - Present

Education

Zhejiang University (ZJU)
Ph.D. in Computer Science                   Feb. 2017 - June 2020, Hangzhou
Advisor: Prof. Chun Chen
Master in Computer Science                   Sep. 2014 - Feb.2017, Hangzhou
Advisor: Prof. Chun Chen
University of Electronic Science and Technology of China (UESTC)
Bachelor in Micro-electronic      Sep 2010 - June 2014, Chengdu

Useful Links

Machine Learning Reading List
Deep Learning Reading List

Last update: Feb. 2, 2022. Webpage template borrows from Xiangnan He.