People: Research Faculty

Sabina Tomkins

Sabina Tomkins

Faculty Associate

Appointments

Faculty Associate, Center for Political Studies
Assistant Professor of Information, School of Information

Degree

Ph.D.  2018 University of California, Santa Cruz (Technology Management)

Other

Sabina Tomkins’s Personal Website

Research

Sabina Tomkins joined UMSI as assistant professor in Fall 2021. Her research applies computational methods to advance understanding in policy relevant domains. Her methods interests include responsible AI, survey design, and causal inference, and she currently works in the domains of computational sustainability, political science, and education policy.

Contact

School of Information
105 S. State Street, Ann Arbor, MI 48109

Phone: 734-76405876
Email: stomkins@umich.edu

University of Michigan Online Directory listing

Selected Publications

Please also see Sabina Tomkins’s Curriculum Vitae (CV).
Tomkins, S., Ramesh, A. and L. Getoor, Predicting Post-Test Performance from Online Student Behavior: A High School MOOC Case Study. (2016) International Educational Data Mining Society.
M Schweinsberg, M Feldman, N Staub, et al., Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis (2021)OrganizationalBehavior and Human Decision Processes 165, 228-249.
Tomkins, S., Isley, S., London, B. and L. Getoor, Sustainability at scale: towards bridging the intention-behavior gap with sustainable recommendations (2018), Proceedings of the 12th ACM conference on recommender systems, 214-218
Tomkins, S., Getoor, L., Chen, Y. and Y. Zhang, A socio-linguistic model for cyberbullying detection (2018) 2018 IEEE/ACM International Conference on Advances in Social Networks
Akkiraju, RKT, Bhuiyan, M., Gundecha, P.S. et al., Recommending a dialog act using model-based textual analysis (2019) US Patent 10,360,908
Tomkins, S., Liao, P., Klasnja, P. and S. Murphy, Intelligentpooling: Practical thompson sampling for mhealth (2021) Machine learning 110 (9), 2685-2727