Hassan Rafique

Assistant Professor

Department of Sport Analytics

Contact

harafiqu@syr.edu

Department

Department of Sport Analytics

Location

Syracuse, New York, 13244

Extras

Pronouns: He, Him

Biography

Hassan Rafique (he/him/his) joined the Department of Sport Analytics in the David B. Falk College of Sport in Fall 2025 as a tenure-track assistant professor. He teaches classes in sport analytics, primarily statistical analysis and machine learning.

Prior to joining Syracuse University, Rafique was an assistant professor of instruction from 2023-25 at the University of Iowa, where he taught programming, machine learning, and visualization. Previously, he served as an assistant professor of data science and the founding director of the Center for Data Science at the University of Indianapolis from 2020-23.

Rafique's research interests are sport analytics, machine learning, and optimization. He specifically focuses on developing advanced methods and tools to estimate and predict the performance of individual players and teams, which is crucial information for team front offices. His work on cricket analytics was recognized at the Carnegie Mellon Sports Analytics Conference and the MIT Sloan Sports Analytics Research Conference. His research has been published at the International Conference on Machine Learning (ICML), Journal of Machine Learning Research, and Optimization Methods and Software.

Rafique won first place in the reproducible research competition at the 2022 Carnegie Mellon Sports Analytics Conference. He received the 2024 Tippie Instructor Award for the business analytics program. His work on interpretable machine learning received a best paper runners-up award at the Data Mining Conference at 2019 INFORMS. He was nominated for the prestigious Hancher Finkbine student medallion in 2019. He received the Outstanding Teaching Assistant award in 2017, and a graduate teaching fellowship in 2018.

Rafique earned a Ph.D. in applied mathematical and computational sciences from the University of Iowa in 2020. He completed an M.S. in mathematics from Western Illinois University in 2015 and a B.S. in mathematics from the Lahore University of Management Sciences in 2012. He attained a Certificate of College Teaching from the University of Iowa in 2019.

Education

Ph.D., The University of Iowa, Iowa City, IA
Office of Graduate Teaching Excellence, The University of Iowa, Iowa City, IA, . Major: Graduate Certificate in College Teaching
M.S., Western Illinois University, Macomb, IL, . Major: Mathematics
B.S., Lahore University of Management Sciences, Lahore, . Major: Mathematics

Teaching

Currently Teaching

SAL 608 - Applications of Machine Learning for Sport Analytics Using R

Published Scholarship

Publications

Rafique, H., Liu, M., Lin, Q. and Yang, T., 2021. Weakly-convex–concave min–max optimization: provable algorithms and applications in machine learning. Optimization Methods and Software, [online] 37(3), pp.1087–1121. https://doi.org/10.1080/10556788.2021.1895152.
Liu, M. et al., 2020. First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems. Journal of Machine Learning, 22(1), pp.7651–7684. Available at: https://www.jmlr.org/papers/volume22/20-533/20-533.pdf.
Rafique, H. et al., 2020. Transparency Promotion with Model-Agnostic Linear Competitors, Available at: https://proceedings.mlr.press/v119/rafique20a.html.
Rafique, H., Lin, Q., Wang, T., Han, W., Burer, S. and Yang, T., n.d. Provable methods for non-convex min-max optimization and models for interpretable machine learning. [online] https://doi.org/10.17077/etd.005549.
Rafique, H., Wang, T. & Lin, Q., 2019. Model-Agnostic Linear Competitors: When Interpretable Models Compete and Collaborate with Black-box Models, Available at: https://amcs.uiowa.edu/news/2019/10/hassan-rafique-received-best-paper-award-runner-informs-workshop-data-science-2019.
Liu, M. et al., 2018. Provable Non-Convex Min-Max Optimization,
Imran, M., Rafique, H., Khan, A. and Malik, T., 2013. A model of bi-mode transmission dynamics of hepatitis C with optimal control. Theory in Biosciences, [online] 133(2), pp.91–109. https://doi.org/10.1007/s12064-013-0197-0.

Presentations

Rafique, H., 2025. Umpires Under Surveillance—Analyzing Triple-A Umpire Performance Under The Challenge System. In Carnegie Mellon Sports Analytics Conference. Carnegie Mellon University.
Rafique, H., 2025. A Comparison of Batter Performance and League Quality Across Domestic T-20 Cricket Leagues. In New England Symposium on Statistics in Sports. Harvard University.
Rafique, H., 2024. Introduction to Sports Analytics. In Iowa Student Sports Analytics Club Organizing Meeting. University of Iowa.
Rafique, H., 2023. cricWAR: A reproducible system for player performance in limited-overs cricket. In MIT Sloan Sports Analytics Competition.
Rafique, H., 2023. A comprehensive framework for evaluating plays and player performance in American Ultimate Disc League. In Team Boston Glory. American Ultimate Disc League.
Rafique, H., 2022. cricWAR: A reproducible system for player performance in limited-overs cricket. In Carnegie Mellon Sports Analytics Competition. Carnegie Mellon University.
Rafique, H., 2022. Introduction to Sports Analytics. In Applied Math and Data Science Seminar. University of Indianapolis.
Rafique, H., 2021. Lessons Learned: A Recent Graduate’s Suggestions for Succeeding After Graduate School. In AAU Initiative Colloquium. The University of Iowa.
Rafique, H., 2019. Model-Agnostic Linear Competitors: When Interpretable Models Compete and Collaborate with Black-box Models. In INFORMS Third Data Science Workshop.
Rafique, H., 2019. Oracle Complexity of a Trust Region Method for Non-Convex Min-Max Problem. In INFORMS Annual Meeting.

Honors, Awards, and Recognition

Instructor of the Year [Master's Program], Tiipie College of Business, The University of Iowa (received: 2025)
’Thank-a-Teacher’ honor, Center for Teaching, The University of Iowa
Finalist, Boston Glory Data Modeling Challenge, Boston Glory, American Ultimate Disc League
Poster Finalist, Research Paper Competition, MIT Sloan Sports Analytics Conference
Best Paper Award, Reproducible Research Competition, Carnegie Mellon Sports Analytics Competition
Best Paper Award Runner-Up, Third INFORMS Workshop on Data Science, INFORMS College on Artificial Intelligence
Graduate & Profession Student Government Travel Grant, The University of Iowa
Hancher-Finkbine Medallion (Nominee), The University of Iowa
Post-Comprehensive Research Fellowship, Graduate College, The University of Iowa
Summer Fellowship, Graduate College, The University of Iowa