Tom Overman
PhD Candidate in Engineering Sciences and Applied Mathematics at Northwestern University
My research is in machine learning with a focus on federated machine learning and automated data science.
Publications
Published, peer-reviewed
- Overman, T., Klabjan, D., & Utke, J. IIFE: Interaction Information Based Automated Feature Engineering in 2024 IEEE International Conference on Data Mining (ICDM), Abu Dhabi, United Arab Emirates (December 2024).
- Overman, T., Blum, G., & Klabjan, D. A Primal-Dual Algorithm for Hybrid Federated Learning in Proc. 38th Annual AAAI Conference on Artificial Intelligence, Vancouver, Canada (February 2024).
- Overman, T. and Pal, S. Statistical Tools and Techniques in Modeling Survival Data. Mathematics Research for the Beginning Student, Volume 2. Springer International Publishing.
- Meyers, I., Munar, J., Neville, E., Overman, T., A Parallel-in-Time Multigrid Approach to Constrained Optimization https://www.osti.gov/servlets/purl/1782532
Preprints, in-progress
- Overman, T. and Klabjan, D., Continuous-Time Analysis of Federated Averaging, Under Review, https://arxiv.org/abs/2501.18870
- Overman, T. and Klabjan, D. Federated Automated Feature Engineering, In progress
Industry Experience
- PhD Data Science Intern at Epsilon, Summer 2024.
- Data Science Engineer Intern at Sabre, Summer 2023.
- Data Science Student Consultant at McKinsey and Company, Jan-Jun 2022.
- Software Developer at Planet Access, Jun 2017-Oct 2020.