Yupeng Gu

Department of Computer Science, UCLA

Office: 3551 Boelter Hall

Email: ypgu AT cs DOT ucla DOT edu




I'm a Ph.D student in Scalable Analytics Institute (ScAi), Department of Computer Science, University of California, Los Angeles (UCLA). My advisor is Prof. Yizhou Sun. Before joining UCLA, I spent three years at Northeastern University, Boston. I received my Bachelor of Science degree in Applied Mathematics, at University of Science and Technology of China.


• My general research interests lie in mining heterogeneous social networks and information networks with social factors.


[Google Scholar Page]

• Rui Dong, Yizhou Sun, Lu Wang, Yupeng Gu, Yuan Zhong, "Weakly-Guided User Stance Prediction via Joint Modeling of Content and Social Interaction", Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM'17), Singapore, Nov, 2017.

• Yupeng Gu, Yizhou Sun, Jianxi Gao, "The Co-Evolution Model for Social Network Evolving and Opinion Migration", Proceedings of the 23th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'17), Halifax, NS, Canada, Aug. 2017. [Paper] [Code and Dataset] [Slides] [Video]

• Yupeng Gu, Ting Chen, Yizhou Sun, Bingyu Wang, "Ideology Detection for Twitter Users with Heterogeneous Types of Links", Proceedings of 2017 International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction (SBP'17), Washington D.C., USA, July, 2017. [Short Version] [Long Version (arxiv)] [Slides]

• Yupeng Gu, Bo Zhao, David Hardtke, Yizhou Sun, "Learning Global Term Weights for Content-based Recommender Systems", Proceedings of the 25th International Conference on World Wide Web (WWW'16), Montreal, QC, Canada, Apr. 2016. [Paper] [Slides]

• Yupeng Gu, Yizhou Sun, Ning Jiang, Bingyu Wang, Ting Chen, "Topic-Factorized Ideal Point Estimation Model for Legislative Voting Network", Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'14), New York, NY, USA, Aug. 2014. [Paper] [Code and Dataset] [Slides]