Department of Computer Science
University of Minnesota, Twin Cities
I am a fifth-year computer science PhD student with GroupLens Research at the University of Minnesota - Twin Cities. I am advised by Haiyi Zhu and Loren Terveen. My research interests lie at the interaction of human-computer interaction, applied machine learning, and system building. Two areas of research include (1) understanding online communi-ties and (2) building intelligent systems.
I conduct quantitative and qualitative analysis on user online behaviors and interactions to guide to build recommender and machine learning systems, with the goal of supporting online user collaboration and activities in a broader context, such as building recommender systems in Wikipedia, collaborative learning platforms for MOOCs, and crowd-powered systems for meeting scheduling.
In my spare time, I enjoy working out, playing basketball, and travelling.
Visiting Carnegie Mellon University in Pittsburgh this Fall and finishing up my dissertation!
Will stay in the Bay Area for another three months - excited to join the search team at Amazon A9 for a fall internship!
Going to join the Analytics team in Google for another summer internship. Looking forward to the life and friend get-togethers in California!
I have been working closely with the Wikipedia community and Wikimedia Foundation over the summer to design and build a recommender system for WikiProjects to socialize newcomers. Check out the Signpost article we published for more detail!
Will join Microsoft Research FUSE Labs this summer! Excited about my second internship and the summer in Seattle!
Very excited to join the IBM Research Center at Yorktown Heights, New York this summer for my first internship! Will be working on social media data analysis!
Ma, H., Cheng, H., Yu, B., Zhu, H. Effects of Anonymity, Ephemerality, and System Routing on Cost in Social Question Asking. In Proceedings of GROUP 2020. Paper PDF
Chen, H., Yu, B., et. al. Teaching UI Design at Global Scales: A Case Study of the Design of Collaborative Capstone Projects for MOOCs. In Proceedings of the ACM on Learning @ Scale 2019. Paper PDF
Zhu, .H, Yu, B., Halfaker, A,. Terveen, L. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proc. of ACM Hum.-Comput. Interact. 1. 2, Article 194. Paper PDF
Karumur, R., Yu, B., Zhu, H., Konstan, J. Content is King, Leadership Lags: Effects of Prior Experience on Newcomer Retention and Productivity in Online Production Groups. In Proceedings of SIGCHI 2018. Paper PDF
Yu, B., Wang, X., Lin, Y., Ren, Y., Terveen, L., Zhu, H. Out With The Old, In With The New? Unpacking Member Turnover in Online Production Groups. Proc. ACM Hum.-Comput. Interact. 1, 2, Article 117. Paper PDF
Cheng, H., Yu, B., Park, Y., Zhu, H. ProjectLens: Supporting Project-based Collaborative Learning on MOOCs. In Proceedings of ACM Learning @ Scale 2017. Paper PDF
Cranshaw, J., Elwany, E., Newman, T., Kocielnik, R., Yu, B., Soni, S, Teevan, J., Monroy-Hernandez, A. Calendar.help: Designing a Workflow-Based Scheduling Agent with Humans in the Loop. In Proceedings of SIGCHI 2017. Paper PDF
Yu, B., Ren, Y., Terveen, L., and Zhu, H. Predicting Member Productivity and Withdrawal from Pre-Joining Attachments in Online Production Groups. In Proceedings of CSCW 2017. Paper PDF
Lin, Y., Yu, B., Hall, A., and Hecht, B. Problematizing and Addressing the Article-as-Concept Assumption in Wikipedia. In Proceedings of CSCW 2017. Paper PDF