- Ph.D (2014)
- Computer Science, University of Minnesota, Minneapolis, MN. Advisers: John T. Riedl and Joseph A. Konstan
- B.S. (2007)
- Computer Engineering (With Distinction), Iowa State University, Ames, IA.
- Assistant Professor, Dept. of Computer Science, Boise State University
- Co-founder, People and Information Research Team (PIReT)
- Assistant Professor, Dept. of Computer Science, Texas State University
- Graduate Research Assistant, GroupLens Research, Dept. of Computer Science, University of Minnesota
- Summer 2010
- Research Intern, Autodesk Research, Toronto, CA
- CS 533 (Introduction to Data Science)
- CS 597 (Recommender Systems)
- CS 410 / CS 510 (Databases)
- Recommender Systems specialization on Coursera
Author formatting key:, , .
2017. The Demographics of Cool: Popularity and Recommender Performance for Different Groups of Users. In RecSys 2017 Poster Proceedings.and .
2017. Sturgeon and the Cool Kids: Problems with Top-N Recommender Evaluation. In Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference.and .
2016. Behaviorism is Not Enough: Better Recommendations through Listening to Users. In Proceedings of the Tenth ACM Conference on Recommender Systems (RecSys '16). ACM. DOI:10.1145/2959100.2959179. Acceptance rate: 36% (Past, Present, and Future track).and .
2015. Letting Users Choose Recommender Algorithms: An Experimental Study. In Proceedings of the Ninth ACM Conference on Recommender Systems (RecSys '15). ACM. DOI:10.1145/2792838.2800195. Acceptance rate: 21%., , , and .
2016. Dependency Injection with Static Analysis and Context-Aware Policy. Journal of Object Technology 15, 1 (February 2016), pp 1:1–31. DOI:10.5381/jot.2016.15.5.a1.and .
2014. User Perception of Differences in Recommender Algorithms. In Proceedings of the Eighth ACM Conference on Recommender Systems (RecSys '14). ACM. DOI:10.1145/2645710.2645737. Acceptance rate: 23%., , , and .
2015. Teaching Recommender Systems at Large Scale: Evaluation and Lessons Learned from a Hybrid MOOC. Transactions on Computer-Human Interaction 22, 2, Article 10 (April 2015), 23 pages. DOI:10.1145/2728171., , , , and .
2013. Rating Support Interfaces to Improve User Experience and Recommender Accuracy. In Proceedings of the Seventh ACM Conference on Recommender Systems (RecSys '13). ACM. DOI:10.1145/2507157.2507188. Acceptance rate: 24%., , , , , , and .
2012. How Many Bits per Rating?. In Proceedings of the Sixth ACM Conference on Recommender Systems (RecSys '12). ACM, pp 99–106. DOI:10.1145/2365952.2365974. Acceptance rate: 20%., , , , and .
2011. Rethinking The Recommender Research Ecosystem: Reproducibility, Openness, and LensKit. In Proceedings of the Fifth ACM Conference on Recommender Systems (RecSys '11). ACM, 133–140. DOI:10.1145/2043932.2043958. Acceptance rate: 27% (20% for oral presentation, which this received)., , , and .
2011. Collaborative Filtering Recommender Systems. Foundations and Trends® in Human-Computer Interaction 4, 2 (February 2011), pp 81–173. DOI:10.1561/1100000009., , and .
2011. Searching for Software Learning Resources Using Application Context. In Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology (UIST '11). ACM, 195–204. DOI:10.1145/2047196.2047220. Acceptance rate: 25%., , , , and .
2010. Automatically Building Research Reading Lists. In Proceedings of the Fourth ACM Conference on Recommender Systems (RecSys '10). ACM, 159–166. DOI:10.1145/1864708.1864740. Acceptance rate: 19%., , , , , and .
- 2014 Texas State University Research Enhancement Program (competitive internal research grant), $8000: Temporal Analysis of Recommender Systems.
- ACM Conference on Recommender Systems (General Co-chair 2018, Steering Committee since 2017, PC member since 2014, Publicity Co-chair 2016, Demos Co-chair 2012)
- Conference on Fairness, Accountability, and Transparency (Steering Committee, Systems Track co-chair 2018)
- Distinguished Reviewer, ACM Transactions on Interactive Intelligent Systems (2017–present)
- Organizer, FATREC Workshop on Responsible Recommendation at RecSys 2017
- Program committee, ACM WWW Track on Behavior Analysis and Personalization (2016, 2017)
- External advisor, CrowdRec (EU Framework Programme collaborative research project, 2014–2016)
- PC member and/or reviewer for numerous conferences, including WWW (Track on Behavior Analysis and Personalization), FLAIRS Special Track on Recommender Systems, CHI, CSCW, IUI, SAC REcommender Systems track, UIST, WikiSym/OpenSym, ICWSM
- Reviewer for multiple journals, including TIST, TOIS, TWEB, TKDD, TIIS, TDSC, TKDE, PLOS ONE, and UMUAI
- Proceedings co-chair, ACM CHI 2012–2013