Conference

• Bhowmik, R., Ponza, M., Tendle, A., Gupta, A., Jiang, R., Lu, X., Zhao, Q. and Preoţiuc-Pietro, D., 2024, June. Leveraging Contextual Information for Effective Entity Salience Detection. In Findings of the Association for Computational Linguistics: NAACL 2024 (pp. 395-408).
• Kotkov, D., Zhao, Q., Launis, K. and Neovius, M., 2020, September. ClusterExplorer: Enable User Control over Related Recommendations via Collaborative Filtering and Clustering. In Fourteenth ACM Conference on Recommender Systems (RecSys'20) (pp. 432-437).
• Wang, H., Zhao, Q., Wu, Q., Chopra, S., Khaitan, A. and Wang, H., 2020, September. Global and Local Differential Privacy for Collaborative Bandits. In Fourteenth ACM Conference on Recommender Systems (RecSys'20) (pp. 150-159).
• Zhao, Qian, Martijn Willemsen, Gediminas Adomavicius, F. Maxwell Harper, Joseph A. Konstan. 2019. From Preference into Decision Making: Modeling User Interactions in Recommender Systems. In Proceedings of The 13th ACM Conference on Recommender Systems (RecSys ’19). ACM, New York, NY, USA.
• Zhao, Qian, Martijn Willemsen, Gediminas Adomavicius, F. Maxwell Harper, Joseph A. Konstan. 2018. Interpreting User Inaction in Recommender Systems. In Proceedings of The 12th ACM Conference on Recommender Systems (RecSys ’18). ACM, New York, NY, USA.
• Zhao, Qian, Jilin Chen, Minmin Chen, Sagar Jain, Alex Beutel, Francois Belletti, Ed Chi. 2018. Categorical-Attributes-Based Item Classification for Recommender Systems. In Proceedings of The 12th ACM Conference on Recommender Systems (RecSys ’18). ACM, New York, NY, USA.
• Zhong, Yifan, Tahir Lazaro Sousa Menezes, Vikas Kumar, Qian Zhao, F. Maxwell Harper. 2018. A Field Study of Related Video Recommendations: Newest, Most Similar, or Most Relevant. Short paper In Proceedings of The 12th ACM Conference on Recommender Systems (RecSys ’18). ACM, New York, NY, USA.
• Zhao, Qian, Paul N. Bennett, Adam Fourney, Anne Loomis Thompson, Shane Williams, Adam D. Troy, Susan T. Dumais. 2018. Calendar-Aware Proactive Email Recommendation. In Proceedings of The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR ’18). ACM, New York, NY, USA.
• Zhao, Qian, F. Maxwell Harper, Gediminas Adomavicius, Joseph Konstan. Explicit or Implicit Feedback? Engagement or Satisfaction? A Field Experiment on Machine-Learning-Based Recommender Systems. In Proceedings of the 33rd ACM/SIGAPP Symposium On Applied Computing, Track of Recommender Systems: Theory, User Interactions and Applications (SAC 2018), ACM, 2018.
• Kotkov, Denis, Joseph A. Konstan, Qian Zhao, Jari Veijalainen. Investigating Serendipity in Recommender Systems Based on Real User Feedback. In Proceedings of the 33rd ACM/SIGAPP Symposium On Applied Computing, Track of Recommender Systems: Theory, User Interactions and Applications (SAC 2018), ACM, 2018.
• Zhao, Qian, Yue Shi, Liangjie Hong. GB-CENT: Gradient Boosted Categorical Embedding and Numerical Trees. In Proceedings of the 26th International World Wide Web conference (WWW 2017), ACM, 2017.
• Zhao, Qian, Sashank Varma, Joseph A. Konstan. In-video Reuse of Discussion Threads in MOOCs. Short paper In Proceedings of the Fourth Annual ACM Conference on Learning at Scale (L@S 2017), ACM, 2017.
• Zhao, Qian, Gediminas Adomavicius, F. Maxwell Harper, Martijn Willemsen, Joseph A. Konstan. Toward Better Interactions in Recommender Systems: Cycling and Serpentining Approaches for Top-N Item Lists. In Proceedings of the 20th ACM conference on Computer supported cooperative work & social computing (CSCW 2017), ACM, 2017.
• Zhao, Qian, Shuo Chang, F. Maxwell Harper, Joseph A. Konstan. Gaze Prediction for Recommender Systems. In Proceedings of the 10th ACM Conference on Recommender Systems (RecSys 2016), ACM, 2016.
• Zhao, Qian, Zihong Huang, F. Maxwell Harper, Loren Terveen, Joseph A. Konstan. Precision CrowdSourcing: Closing the Loop to Turn Information Consumers into Information Contributors. In Proceedings of the 19th ACM conference on Computer supported cooperative work & social computing (CSCW 2016), ACM, 2016.

Ph.D. Thesis

• Zhao, Qian. 2018. User-Centric Design and Evaluation of Online Interactive Recommender Systems. Ph.D. Thesis. University of Minnesota.

Workshop

• Zhao, Qian. Artifact-centered Q&As for Learning. The 3rd Annual Learning Science Workshop Research and Innovation for Enhancing Achievement and Equity. 2014
• Dong, Zhenhuang, Qian Zhao, 2012, August. Experimental analysis on cross domain preferences association and rating prediction. In Proceedings of the 1st International Workshop on Cross Domain Knowledge Discovery in Web and Social Network Mining (pp. 26-31). ACM.