News
16 Jan 2021
One full paper is accepted by WWW 2021, about graph neural network for knowledge graph-aware recommendation.
23 April 2020
One full paper is accepted by SIGIR 2020, about graph neural network for recommendation.
11 Jan 2020
One full paper is accepted by WWW 2020, about knowledge graph-reinforced negative sampling.
29 April 2019
One full paper is accepted by KDD 2019, about graph neural network for knowledge-aware recommendation.
14 April 2019
One full paper is accepted by SIGIR 2019, about graph neural network for recommendation.
24 January 2019
I have successfully defended my thesis and got the PhD degree! My thesis title is "Exploiting Cross-Channel Information for Personalized Recommendation".
![]() |
Xiang WANG
Research Fellow
NExT++
Computing 1, Computing Drive, Singapore 117417
Email: xiangwang AT u.nus.edu
|
Xiang Wang is now a research fellow in NExT++, School of Computing, National University of Singapore.
His research interests include information retrieval, data mining, and explainable AI, particularly in recommender systems, graph learning, and social media analysis.
Moreover, he has served as the PC member for top-tier conferences including SIGIR and MM, and the invited reviewer for prestigious journals including TKDE, TOIS, TKDD, and TIST.
Education
National University of Singapore (NUS) Ph.D. in Computer Science July 2014 - February 2019, Singapore Advisor: Prof. Chua Tat-Seng Mentors: Dr. He Xiangnan and Dr. Nie Liqiang |
Beihang University (BUAA) Bachelor in Computer Science and Engineering Sep 2010 - June 2014, Beijing Advisor: Prof. Li Zhoujun |
Experiences
Postdoc Research Fellow, National University of Singapore, February 2019 - Present Advisior: Prof. Chua Tat-Seng (NExT++: NUS-Tsinghua-Southampton Extreme Search Center) |
Research Intern, Institute of Automation, Chinese Academy of Sciences, June 2013 - February 2014 Advisior: Prof. Xu Changsheng and Dr. Fang Quan (National Lab of Pattern Recognition) |
First-Author Publications Google Scholar
In the Year of 2021:![]() |
Learning Intents behind Interactions with Knowledge Graph for Recommendation
Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He & Tat-Seng Chua WWW 2021 (Full, Accept rate: 20.6%) • arXiv • Codes • Slides |
![]() |
Disentangled Graph Collaborative Filtering
Xiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu & Tat-Seng Chua SIGIR 2020 (Full, Accept rate: 26%) • arXiv • Codes • Slides |
![]() |
Reinforced Negative Sampling over Knowledge Graph for Recommendation
Xiang Wang, Yaokun Xu, Xiangnan He, Yixin Cao, Meng Wang & Tat-Seng Chua WWW 2020 (Full, Accept rate: 19%) • arXiv • Codes • Slides |
![]() |
KGAT: Knowledge Graph Attention Network for Recommendation
Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu & Tat-Seng Chua KDD 2019 (Full, Accept rate: 14.2%) • arXiv • Codes • Slides |
![]() |
Neural Graph Collaborative Filtering
Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng & Tat-Seng Chua SIGIR 2019 (Full, Accept rate: 20%) • arXiv • Codes • Slides |
![]() |
Explainable Reasoning over Knowledge Graph Paths for Recommendation
Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao & Tat-Seng Chua AAAI 2019 (Full, Accept rate: 16.2%) • arXiv • Codes • Slides |
![]() |
TEM: Tree-enhanced Embedding Model for Explainable Recommendation
Xiang Wang, Xiangnan He, Fuli Feng, Liqiang Nie & Tat-Seng Chua WWW 2018 (Accept rate: 14.8%) • Codes • Slides |
![]() |
Item Silk Road: Recommending Items from Information Domains to Social Users
Xiang Wang, Xiangnan He, Liqiang Nie & Tat-Seng Chua SIGIR 2017 (Accept rate: 22%) • Codes • Slides |
![]() |
Unifying Virtual and Physical Worlds: Learning towards Local and Global Consistency
Xiang Wang, Liqiang Nie, Xuemeng Song, Dongxiang Zhang & Tat-Seng Chua ACM Transactions on Information Systems (TOIS) • Codes • Slides |
Tutorials
![]() |
Bias Issues and Solutions in Recommender System
Jiawei Chen, Xiang Wang, Fuli Feng & Xiangnan He WWW 2021 Slides (2021/04) |
![]() |
Learning and Reasoning on Graph for Recommendation
Xiang Wang, Xiangnan He & Tat-Seng Chua WSDM 2020 Slides (2020/01 @ Houston, Texas, US) |
![]() |
Learning and Reasoning on Graph for Recommendation
Xiang Wang, Xiangnan He & Tat-Seng Chua CIKM 2019 Slides (2019/11 @ Beijing, China) |
Honors
Dean’s Graduate Research Excellence Award, June 2018
- School of Computing, National University of Singapore |
Research Achievement Award, June 2017
- School of Computing, National University of Singapore |
Full Research Scholarship, 2014-2019
- National University of Singapore |
Excellent Graduates, May 2014
- Beihang University, China |
National Scholarship (top scholarship for Chinese undergraduates), December 2013
- Beihang University, China |
Invited Talks
Explainable Reasoning over Knowledge Graph Paths for Recommendation
- Shandong University, Augest 11, 2018 (invited by Prof. Nie Liqiang) |
TEM: Tree-enhanced Embedding Model for Explainable Recommendation
- 6estate Company, Singapore, October 11, 2018 (invited by Dr. Luan Huanbo & Dr. Wang Chao) - WWW 2018, Lyon, France, April 26, 2018 |
Item Silk Road: Recommending Items from Information Domains to Social Users
- Shandong University, May 20, 2017 (invited by Prof. Nie Liqiang) - SIGIR 2017, Tokyo, Japan, August 5, 2017 |
Professional Services
Program Committee Member of KDD (2021) Program Committee Member of WWW (2020,2021) Program Committee Member of ACM SIGIR (2019,2020,2021) Program Committee Member of ACM MM (2019,2020) Invited Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE) Invited Reviewer for ACM Transactions on Information Systems (TOIS) Invited Reviewer for ACM Transactions on Intelligent Systems and Technology (TIST) Invited Reviewer for ACM Transactions on Knowledge Discovery from Data (TKDD) Invited Reviewer for Information Sciences Invited Reviewer for Neurocomputing Invited Reviewer for Frontiers of Computer Science Invited Reviewer for World Wide Web Journal (WWWJ) Invited Reviewer for Multimedia Systems Journal (MMSJ) External Reviewer of SIGIR 2016-2018, WWW 2017-2019. |
Useful Links
NUS CS Conference Rankings |
NUS CS Journal Ranking |
NUS CS Courses |
Machine Learning Reading List |
Deep Learning Reading List |
Last update: May 1, 2019. Webpage template borrows from Xiangnan He.