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. He received his PhD in Electrical Engineering from the Massachusetts Institute of Technology in 2019, where he was fortunate to be advised by David Gamarnik and John Tsitsiklis. Before that, he received a M.Sc. in Engineering and a B.Sc. in Electronics Engineering from Universidad ORT Uruguay.
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 he can combine traditional model-based analysis with newer data-centric approaches to get the best of both worlds. He was a finalist for the 2019 INFORMS APS Best Student Paper Award, and for the 2016 INFORMS George E. Nicholson Student Paper Competition.
More information can be found on Zubeldía's personal website.
Education
Ph.D., Massachusetts Institute of Technology, Electrical Engineering, 2019
M.S., Universidad ORT Uruguay, Engineering, 2014
B.S., Universidad ORT Uruguay, Electronics Engineering, 2012
