Professor Sen's research is in designing systems that empower people to be
effective online community contributors. His research draws on techniques from
data-mining, machine learning, systems design, human-computer interaction, and Social
Science theory. 

His interests range from collaborative filtering algorithms research to intelligent
displays of user-created tags - specifically, building software systems, applying data
mining and machine learning techniques on huge data sets, and writing software apps that
touch a large number of users. 



Getting to the Source: Where does Wikipedia Get Its Information? (with Heather Ford, David R. Musicant, and Nathaniel Miller), Proceedings of the 9th International Symposium on Open Collaboration (2013)


How many bits per rating? (with D Kluver, T Nguyen, M Ekstrand, and J Riedl), RecSys'12 (2012)


The Tag Genome: Encoding Community Knowledge to Support Novel Interaction (with J Vig and J Riedl), ACM Transactions on Interactive Intelligent Applications (2012)


Recommending Routes in the Context of Bicycling: Algorithms, Evaluation, and the Value of Personalization (with R Preidhosky, D Pitchford, and L Terveen), CSCW'12 ACM 2012 Conference on Computer Supported Cooperative Work (2012)


War Versus Inspirational in Forrest Gump: Cultural Effects in Tagging Communities (with Z Dong, C Shi, L Terveen, and J Riedl), ICWSM 2012, Sixth International AAAI Conference on Weblogs and Social Media (2012)

Contributions to Books


“Collaborative Filtering Recommender Systems” (with Shafer, Frankowski, and Herlocker), The Adaptive Web: Methods and Strategies of Web Personalization (2007)


Tagsplanations: Explaining Recommendations using Tags (with Jesse Vig and John Riedl), International Conference on Intelligent User Interfaces (2009)

Crafting the initial user experience to achieve community goals (with Sara Drenner and Loren Terveen), ACM Recommender Systems (2008)