Thiago Serra

Thiago Serra

Assistant Professor of Analytics & Operations Management
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About Thiago Serra

Education

  • Ph.D., Operations Research, Carnegie Mellon University, 2018.
  • M.S., Carnegie Mellon University, 2015.
  • M.S., University of Sao Paulo, 2012.
  • B.S., University of Campinas, 2008.

Recent and Representative Publications

Serra, T., Huang, T., Raghunathan, A., & Bergman, D. (accepted). Template-based Minor Embedding for Adiabatic Quantum Optimization. INFORMS Journal on Computing.

Serra, T. (2020). Reformulating the disjunctive cut generating linear program. Annals of Operations Research, 295(1), 363–384. http://dx.doi.org/10.1007/s10479-020-03709-2

Serra, T., & Hooker, J. N. (2020). Compact representation of near-optimal integer programming solutions. Mathematical Programming, 182(1), 199–232. dx.doi.org/10.1007/s10107-019-01390-3

Balas, E., & Serra, T. (2020). When Lift-and-Project Cuts are Different. INFORMS Journal on Computing, 32(3), 822–834. https://doi.org/10.1287/ijoc.2019.0943

Serra, T. (2020). Enumerative Branching with Less Repetition. In N. Hebrard Emmanuel Musliu (Ed.), Integration of Constraint Programming, Artificial Intelligence, and Operations Research (pp. 399–416). Springer International Publishing. doi.org/10.1007/978-3-030-58942-4_26

Serra, T., Kumar, A., & Ramalingam, S. (2020). Lossless Compression of Deep Neural Networks. In N. Hebrard Emmanuel Musliu (Ed.), Integration of Constraint Programming, Artificial Intelligence, and Operations Research (pp. 417–430). Springer International Publishing. doi.org/10.1007/978-3-030-58942-4_27

Serra, T., & O'Neil, R. J. (2020). MIPLIBing: Seamless Benchmarking of Mathematical Optimization Problems and Metadata Extensions. SN Operations Research Forum, 1(3), 24. doi.org/10.1007/s43069-020-00024-1

Serra, T., & Ramalingam, S. (2020). Empirical Bounds on Linear Regions of Deep Rectifier Networks. The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, 34, 5628–5635. doi.org/10.1609/aaai.v34i04.6016

Serra, T., Raghunathan, A. U., Bergman, D., Hooker, J., & Kobori, S. (2019). Last-Mile Scheduling Under Uncertainty. In K. Rousseau Louis-Martin Stergiou (Ed.), Integration of Constraint Programming, Artificial Intelligence, and Operations Research (pp. 519--528). Springer International Publishing. link.springer.com/chapter/10.1007/978-3-030-19212-9_34

Serra, T., Tjandraatmadja, C., & Ramalingam, S. (2018). Bounding and Counting Linear Regions of Deep Neural Networks. In A. Dy Jennifer Krause (Ed.), Proceedings of the 35th International Conference on Machine Learning: Vol. 80 (pp. 4558--4566). PMLR. proceedings.mlr.press/v80/serra18b.html

Raghunathan, A. U., Bergman, D., Hooker, J., Serra, T., & Kobori, S. (2018). The integrated last-mile transportation problem (ILMTP). Twenty-Eighth International Conference on Automated Planning and Scheduling. Published.

Recent Courses Taught

  • ANOP 203, Introduction to Programming for Business Analytics.
  • ANOP 102, Spreadsheet Modeling and Data Analysis.

Awards and Honors

  • Gerald L. Thompson Dissertation Award in Management Science, Carnegie Mellon University. (2018).

Further Information

Contact Details

Location

216 Holmes Hall