Hongwei Wang Postdoctoral Researcher Computer Science Department, Stanford University Office: Room 414, William Gates Building Email: hongweiw@cs.stanford.edu CV • Google Scholar • GitHub • LinkedIn • Zhihu

Bio

• Hongwei Wang is now a postdoctoral researcher in Computer Science Department, Stanford University. His research interests include machine learning and data mining, particularly in graph representation learning mechanisms, algorithms and their applications in real-world data mining scenarios such as knowledge graphs, recommender systems, social networks, and sentiment analysis.
• Hongwei Wang received Ph.D. degree from Department of Computer Science and Engineering, Shanghai Jiao Tong University in 2018, and B.E. degree from ACM Class, Shanghai Jiao Tong University in 2014 (with minor in Finance). He was an intern at Microsoft Research Asia. He was one of the recipients of 2018 Google PhD Fellowship.

News

• [02/17/2020] Two preprints available at arXiv! Unifying Graph Convolutional Neural Networks and Label Propagation and Entity Context and Relational Paths for Knowledge Graph Completion.
• [06/28/2019] I give a talk "Knowledge-graph-aware Recommender Systems" at JD.COM Silicon Valley Research Center.
• [04/29/2019] One paper is accepted by KDD 2019: "Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems".

Selected Publications

2019

Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems.
Hongwei Wang, Fuzheng Zhang, Mengdi Zhang, Jure Leskovec, Miao Zhao, Wenjie Li, Zhongyuan Wang.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019.
[Paper] [arXiv] [Code]

Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation.
Hongwei Wang, Fuzheng Zhang, Miao Zhao, Wenjie Li, Xing Xie, Minyi Guo.
The Web Conference (WWW), 2019.
[Paper] [arXiv] [Code]

2018

RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems.
Hongwei Wang, Fuzheng Zhang, Jialin Wang, Miao Zhao, Wenjie Li, Xing Xie, Minyi Guo.
ACM Conference on Information and Knowledge Management (CIKM), 2018.
[Paper] [arXiv] [Code]

DKN: Deep Knowledge-Aware Network for News Recommendation.
Hongwei Wang, Fuzheng Zhang, Xing Xie, Minyi Guo.
The Web Conference (WWW), 2018.
[Paper] [arXiv] [Code]

GraphGAN: Graph Representation Learning with Generative Adversarial Nets.
Hongwei Wang, Jia Wang, Jialin Wang, Weinan Zhang, Miao Zhao, Fuzheng Zhang, Xing Xie, Minyi Guo.
AAAI Conference on Artificial Intelligence (AAAI), 2018.
[Paper] [arXiv] [Code]

SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction.
Hongwei Wang, Fuzheng Zhang, Min Hou, Xing Xie, Minyi Guo, Qi Liu.
ACM Conference on Web Search and Data Mining (WSDM), 2018.
[Paper] [arXiv]

2017

Joint Topic-Semantic-aware Social Recommendation for Online Voting.
Hongwei Wang, Jia Wang, Miao Zhao, Jiannong Cao, Minyi Guo.
ACM Conference on Information and Knowledge Management (CIKM), 2017.
[Paper] [arXiv] [Code]

Honors

• Google Ph.D. Fellowship (6 in East Asia, 57 in total), 2018.
• National Scholarship (ranking: 1st/~200), 2018.
• The 5th place in RecsysChallenge, 2017.
• Outstanding Doctoral Freshman Scholarship, 2014.
• Shanghai Jiao Tong University Outstanding Undergraduate, 2014.
• The 1st prize of National Senior High School Mathematics Contest, 2009.

Media Coverage

• Jiangmen: Knowledge-graph-aware Recommender Systems.
• Boyu College of AI: Exclusive Interview with ACM Class Alumni Hongwei Wang.
• Xinmin Evening News: "A-Class Project" in World Artificial Intelligence Conference.
• MSRA News: Hongwei: "MSRA is the Best Place for CS PhD in China".
• MSRA News: Introduction to the Six Papers Accepted by WWW 2019.
• Fudan Knowledge Workshop: Network Representation Learning Based Recommender Systems.
• SJTU News: CS PhD Candidate Hongwei Wang Won 2018 Google PhD Fellowship.
• Sohu News: Recipients of 2018 Google PhD Fellowship Announced.
• AI Finance: No. 5 Dan Ling Street.
• MSRA News: Knowledge Graph Enhanced Recommender Systems.
• MSRA News: How to Apply Knowledge Graph to Recommender Systems?
• PaperWeekly: GAN in Network Representation Learning.

Invited Talks

• Knowledge-graph-aware Recommender Systems, at JD.COM Silicon Valley Research Center, June 2019, Mountain View.
• When Recommender System Meets Network Representation Learning, at ACM Class Student Academic Festival, June 2018, Shanghai.
• Graph Representation Learning and GraphGAN, at PaperWeekly online talking, January 2018, Beijing.

Professional Activities

• Mentor for Stanford CS341 (Project in Mining Massive Data Sets), Stanford CURIS (Undergraduate Research Internship in Computer Science).
• Teaching assistant for SJTU CS377 (Project Workshop of Database System).
• Program committee member for AAAI (2020), WWW (2020).
• External conference reviewer for WWW (2017, 2018, 2019), KDD (2017, 2018), AAAI (2018, 2019), IJCAI (2018, 2019), CIKM (2017, 2018), DASFAA (2018), SIGIR (2018), MM (2018).
• Journal reviewer for IEEE TNNLS, IEEE TKDE, IEEE Access, IEEE TPAMI, ACM TIST, ACM TWEB, ACM TOIS, Elsevier OSNEM, Elsevier Information Sciences, Elsevier JPDS.
• Research assistant at Hong Kong Polytechnic University.
• Intern at Microsoft Research Asia and Meituan-Dianping Group.

Misc.

• I am a cinephile. Some of my favorite directors are Ang Lee, Quentin Tarantino, Stanley Kubrick, Alfred Hitchcock, and Steven Spielberg. I also like writing reviews.
• I am a fan of Chinese classical poetry. I used to write one when I was in the first year of PhD, after my mom saw me off at the station: