Scholar
Martin Zubeldia
Google Scholar ID: VjcQvJMAAAAJ
University of Minnesota
Citations & Impact
Citations
151
H-index
7
i10-index
7
Publications
20
Co-authors
17
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple journal papers, including in journals such as Operations Research, The Annals of Applied Probability, and Mathematics of Operations Research. Some of his notable works include:
- - Distributed Speed Scaling in Large-Scale Service Systems, with D. Rutten, D. Mukherjee, published in Operations Research (2025).
- - Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise, with Z. Chen, S. T. Maguluri, published in The Annals of Applied Probability (2025).
- - Join-the-Shortest Queue with Abandonment: Critically Loaded and Heavily Overloaded Regimes, with P. R. Jhunjhunwala, S. T. Maguluri, published in Mathematics of Operations Research (2025).
- - Matching Queues with Abandonments in Quantum Switches: Stability and Throughput Analysis, with P. R. Jhunjhunwala, S. T. Maguluri, published in Operations Research (2025).
- - Learning traffic correlations in multi-class queueing systems by sampling queue lengths, with M. Mandjes, published in Performance Evaluation (2022).
- - Stability, memory, and messaging tradeoffs in heterogeneous service systems, with D. Gamarnik, J.N. Tsitsiklis, published in Mathematics of Operations Research (2022).
Research Experience
- Before joining the University of Minnesota, he spent a year as a Postdoctoral Fellow in the department of Industrial and Systems Engineering at the Georgia Institute of Technology, and two years as a Postdoc in the department of Mathematics and Computer Science at the Eindhoven University of Technology and in the Korteweg-de Vries Institute for Mathematics at the University of Amsterdam.
Education
- Received his PhD in Electrical Engineering from the Massachusetts Institute of Technology in 2019, where he was advised by David Gamarnik and John Tsitsiklis.
Background
- Currently an Assistant Professor in the department of Industrial and Systems Engineering (ISyE) at the University of Minnesota. His research primarily focuses on using applied probability for the modeling, analysis, and control of large-scale stochastic decision and learning systems. He is particularly interested in exploring the fundamental tradeoffs between performance, efficiency, and scalability that arise in these systems, and in how we can combine traditional model-based analysis with newer data-centric approaches to get the best of both worlds.
Miscellany
- Contact: zubeldia@umn.edu
