Adolfo Escobedo

Associate Professor

Adolfo Escobedo is an educator and researcher in the field of industrial engineering and operations research. He joined the Edward P. Fitts Department of Industrial and Systems Engineering as an associate professor.

Research Interests

Escobedo’s research interests are in the theory and application of mathematical programming and computing, specifically in the design and analysis of algorithms for power systems operations and planning, circular economy, computational social choice, and computational linear algebra.

Education

DegreeProgramSchoolYear
Ph.D.Doctor of Philosophy in Industrial EngineeringTexas A&M University2016
BAMBachelor of Arts in MathematicsCalifornia State University-Los Angeles2009

Awards and Honors

  • 2024 | NSF Faculty Early Career Development (CAREER) Award
  • 2023 | INFORMS Minority Issues Forum (MIF) Early Career Award
  • 2023 | IISE Operations Research Track Best Paper Award
  • 2021 | INFORMS Computing Society (ICS) Prize
  • 2020 | Top 5% Best Teacher (Arizona State University)
  • 2016 | U.S. Senator Phil Gramm Doctoral Fellowship (Texas A&M University)
  • 2015 | Finalist for the INFORMS Junior Faculty Forum Paper Competition
  • 2015 | Jimmy H. Smith, Ph.D., P.E. Graduate Scholarship (Texas A&M University)
  • 2014 | Energy Institute/Conoco Phillips Fellowship (Texas A&M University)
  • 2012 | Graduate Fellowship (Texas A&M University)
  • 2012 | LSAMP Bridge to the Doctorate Fellowship (Texas A&M University)

 

Discover more about Adolfo R. Escobedo

 

Publications

Heuristic Methods for Top-k List Aggregation Under the Generalized Kendall Tau Distance
Akbari, S., Abdelhadi, A., & Escobedo, A. R. (2026), In Lecture notes in computer science. https://doi.org/10.1007/978-3-032-20537-7_2
Why Districting Becomes NP-hard
Jost, N., Escobedo, A., & Kirchheim, A. (2026, January 1), SSRN Electronic Journal, Vol. 1. https://doi.org/10.2139/ssrn.6102548
Data-driven robust transmission expansion planning against rising temperatures*
Skolfield, J. K., Alnakhli, A., Alawad, A., Escobedo, A. R., & Dehghanian, P. (2025, February 24), Environmental Research Infrastructure and Sustainability, Vol. 5. https://doi.org/10.1088/2634-4505/adb5b3
Whose Wisdom? Human Biases for Decision Support System Source and Scale
Miller, C. M., Patton, C. E., Escobedo, A. R., & Guzman-Bonilla, E. (2025, August 9), Proceedings of the Human Factors and Ergonomics Society Annual Meeting. https://doi.org/10.1177/10711813251360707
Elicitation and aggregation of multimodal estimates improve wisdom of crowd effects on ordering tasks
Yoo, Y., Escobedo, A. R., Kemmer, R., & Chiou, E. (2024, February 1), Scientific Reports, Vol. 14. https://doi.org/10.1038/s41598-024-52176-3
Predicting the composition of solid waste at the county scale
Grassel, J. T., Escobedo, A. R., & Buch, R. (2024, December 17), Waste Management, Vol. 193, pp. 293–306. https://doi.org/10.1016/j.wasman.2024.12.002
Approximate Condorcet Partitioning: Solving large-scale rank aggregation problems
Akbari, S., & Escobedo, A. R. (2023, February 2), Computers & Operations Research. https://doi.org/10.1016/j.cor.2023.106164
Assessing the Effects of Expanded Input Elicitation and Machine Learning-Based Priming on Crowd Stock Prediction
Bhogaraju, H., Jain, A., Jaiswal, J., & Escobedo, A. R. (2023), In Communications in computer and information science (Vol. 1864, pp. 3–16). https://doi.org/10.1007/978-3-031-41774-0_1
Beyond kemeny rank aggregation: A parameterizable-penalty framework for robust ranking aggregation with ties
Akbari, S., & Escobedo, A. R. (2023, May 9), Omega. https://doi.org/10.1016/j.omega.2023.102893
Code and Data Repository for Exact Matrix Factorization Updates for Nonlinear Programming
Escobedo, A. R. (2023, September 6), INFORMS Journal on Computing. https://doi.org/10.1287/ijoc.2021.0331.cd

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Adolfo Escobedo