News


29 Sep 2021
One full paper is accepted by NeurIPS 2021, about explainability in graph neural network.

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 

Professor

School of Cyber Science and Technology
School of Information Science and Technology
University of Science and Technology of China

100, Fuxing Road, Hefei, China

Email: xiangwang1223 AT gmail.com
Google ScholarGitHub

Xiang Wang is a Professor in University of Science and Technology of China. His research interests include information retrieval, data mining, and explainable AI, particularly in recommender systems, graph learning, and social media analysis. He has about 40 publications appeared in several top conferences (e.g., NeurIPS, ICLR, SIGIR, WWW, KDD, CVPR) and journals (e.g., TKDE, TOIS). Moreover, he has served as the PC member for top-tier conferences including NeurIPS, ICLR, SIGIR and KDD, and the invited reviewer for prestigious journals including JMLR, TKDE, TOIS, TKDD, and TIST.


Advertisements
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
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)
- 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.

!

Selected Publications Google Scholar


In the Year of 2022:


pdf
Invariant Grounding for Video Question Answering
Yicong Li, Xiang Wang*, Junbin Xiao, Wei Ji & Tat-Seng Chua
CVPR 2022 (Full, Accept rate: 26%)
  • arXiv    • Codes    • Slides    *Corresponding author

pdf
Discovering Invariant Rationales for Graph Neural Networks
Yingxin Wu, Xiang Wang*, An Zhang, Xiangnan He & Tat-Seng Chua
ICLR 2022 (Full, Accept rate: 26%)
  • arXiv    • Codes    • Slides    *Corresponding author

pdf
ShadeWatcher: Recommendation-guided Cyber Threat Analysis using System Audit Records
Jun Zeng, Xiang Wang*, Jiahao Liu, Yinfang Chen, Zhenkai Liang*, Tat-Seng Chua & Zheng Leong Chua
IEEE S&P 2022 (Full, Accept rate: 26%)
  • arXiv    • Codes    • Slides    *Corresponding author
In the Year of 2021:


pdf
Towards Multi-Grained Explainability for Graph Neural Networks
Xiang Wang, Yingxin Wu, An Zhang, Xiangnan He & Tat-Seng Chua
NeurIPS 2021 (Full, Accept rate: 26%)
  • arXiv    • Codes    • Slides   

pdf
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   
In the Year of 2020:


pdf
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   

pdf
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   
In the Year of 2019:


pdf
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   

pdf
Neural Graph Collaborative Filtering
Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng & Tat-Seng Chua
SIGIR 2019 (Full, Accept rate: 20%)
  • arXiv    • Codes    • Slides   

pdf
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   
In the Year of 2018:


pdf
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   
In the Year of 2017:


pdf
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   

pdf
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  
Look for the full publication list? Please see my CV or visit Google Scholar.

Tutorials


pdf
Bias Issues and Solutions in Recommender System
Jiawei Chen, Xiang Wang, Fuli Feng & Xiangnan He
WWW 2021    Slides (2021/04)   

pdf
Learning and Reasoning on Graph for Recommendation
Xiang Wang, Xiangnan He & Tat-Seng Chua
WSDM 2020    Slides (2020/01 @ Houston, Texas, US)   

pdf
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.

Experiences

Senior Research Fellow, National University of Singapore, July 2021 - Feb 2022
Advisior: Prof. Chua Tat-Seng (NExT++: NUS-Tsinghua-Southampton Extreme Search Center)
Postdoc Research Fellow, National University of Singapore, February 2019 - July 2021
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)

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

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.