Education
- Ph.D (2014)
- Computer Science, University of Minnesota, Minneapolis, MN.
- B.S. (2007)
- Computer Engineering, Iowa State University, Ames, IA.
Appointments
- 2023–present
- Assistant Professor, Dept. of Information Science, Drexel University
- 2022–2023
- Associate Professor, Dept. of Computer Science, Boise State University
- 2016–2022
- Assistant Professor, Dept. of Computer Science, Boise State University
- 2014–2016
- Assistant Professor, Dept. of Computer Science, Texas State University
Research
External Funding
- 2023–2025: NSF 22-32553: Collaborative Research: CCRI: New: A Research News Recommender Infrastructure with Live Users for Algorithm and Interface Experimentation ($1.4M, my share $150K).
- 2018–2023: NSF 17-51278: CAREER: User-Based Simulation Methods for Quantifying Sources of Error and Bias in Recommender Systems. ($514,081, including REU supplements).
Selected Publications
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and . 2024. Towards Optimizing Ranking in Grid-Layout for Provider-side Fairness. Proc. ECIR ’24 (IR for Good track). DOI 10.1007/978-3-031-56069-9_7. NSF PAR 10497109. Acceptance rate: 35.9%.
, , and . 2024. Distributionally-Informed Recommender System Evaluation. TORS 2(1) (March 7th, 2024). DOI 10.1145/3613455. arXiv:2309.05892 [cs.IR]. NSF PAR 10461937. Cited 11 times. Cited 5 times.
, , , and . 2023. Much Ado About Gender: Current Practices and Future Recommendations for Appropriate Gender-Aware Information Access. Proc. CHIIR ’23. DOI 10.1145/3576840.3578316. arXiv:2301.04780. NSF PAR 10423693. Acceptance rate: 39.4%. Cited 14 times. Cited 10 times.
, , , and . 2022. Fairness in Information Access Systems. FnT IR 16(1–2) (July 11th, 2022). DOI 10.1561/1500000079. arXiv:2105.05779 [cs.IR]. NSF PAR 10347630. Impact factor: 8. Cited 147 times. Cited 72 times.
and . 2022. Measuring Fairness in Ranked Results: An Analytical and Empirical Comparison. Proc. SIGIR ’22. DOI 10.1145/3477495.3532018. NSF PAR 10329880. Acceptance rate: 20%. Cited 49 times. Cited 36 times.
and . 2021. Exploring Author Gender in Book Rating and Recommendation. UMUAI 31(3) (February 4th, 2021). DOI 10.1007/s11257-020-09284-2. arXiv:1808.07586v2. NSF PAR 10218853. Impact factor: 4.412. Cited 179 times. Cited 93 times (shared with RecSys18◊).
, , , , , and . 2021. Estimation of Fair Ranking Metrics with Incomplete Judgments. Proc. TheWebConf 2021. DOI 10.1145/3442381.3450080. arXiv:2108.05152. NSF PAR 10237411. Acceptance rate: 21%. Cited 40 times. Cited 34 times.
, , , , and . 2020. Evaluating Stochastic Rankings with Expected Exposure. Proc. CIKM ’20. DOI 10.1145/3340531.3411962. arXiv:2004.13157 [cs.IR]. NSF PAR 10199451. Acceptance rate: 20%. Nominated for Best Long Paper. Cited 174 times. Cited 154 times.
. 2020. LensKit for Python: Next-Generation Software for Recommender Systems Experiments. Proc. CIKM ’20 (Resource track). DOI 10.1145/3340531.3412778. arXiv:1809.03125 [cs.IR]. NSF PAR 10199450. No acceptance rate reported. Cited 85 times. Cited 61 times.
, , and . 2020. Enhancing Classroom Instruction with Online News. AJIM 72(5) (June 15th, 2020). DOI 10.1108/AJIM-11-2019-0309. Impact factor: 1.903. Cited 16 times. Cited 11 times.
, , , , , , and . 2018. All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and Effectiveness. Proc. FAT* 2018. Acceptance rate: 24%. Cited 265 times. Cited 200 times.
, , and . 2018. Privacy for All: Ensuring Fair and Equitable Privacy Protections. Proc. FAT* 2018. Acceptance rate: 24%. Cited 97 times. Cited 71 times.
and . 2016. Behaviorism is Not Enough: Better Recommendations through Listening to Users. Proc. RecSys ’16 (Past, Present, and Future track). DOI 10.1145/2959100.2959179. Acceptance rate: 36%. Cited 131 times. Cited 90 times.
, , , and . 2015. Letting Users Choose Recommender Algorithms: An Experimental Study. Proc. RecSys ’15. DOI 10.1145/2792838.2800195. Acceptance rate: 21%. Cited 136 times. Cited 99 times.
, , , and . 2014. User Perception of Differences in Recommender Algorithms. Proc. RecSys ’14. DOI 10.1145/2645710.2645737. Acceptance rate: 23%. Cited 272 times. Cited 182 times.
, , , and . 2011. Rethinking The Recommender Research Ecosystem: Reproducibility, Openness, and LensKit. Proc. RecSys ’11. DOI 10.1145/2043932.2043958. Acceptance rate: 27% (20% for oral presentation, which this received). Cited 248 times. Cited 194 times.
, , and . 2011. Collaborative Filtering Recommender Systems. FnT HCI 4(2) (February 1st, 2011). DOI 10.1561/1100000009. Cited 1669 times. Cited 651 times.
, , , , and . 2011. Searching for Software Learning Resources Using Application Context. Proc. UIST ’11. DOI 10.1145/2047196.2047220. Acceptance rate: 25%. Cited 56 times. Cited 48 times.
Professional Service & Memberships
- Senior Member, Association for Computing Machinery
- Associate editor, ACM Transactions on Recommender Systems
- Editorial board, Foundations and Trends in Information Retrieval
- Co-organizer, TREC 2019–2021 Track on Fairness in Information Retrieval
- ACM Conference on Recommender Systems (Program Co-chair 2022, General Co-chair 2018, Steering Committee & SPC member)
- Conference on Fairness, Accountability, and Transparency (FAccT) (Executive Committee 2020–2023, Steering Committee 2017–2023, Network Co-chair, PC 2017–present)
- Organizer, FATREC Workshop on Responsible Recommendation at RecSys 2017/2018/2020
- AC for SIGIR, FAccT; SPC for RecSys; numerous other reviews