Victor M. Preciado is with the Departments of Electrical and Systems Engineering and Computer and Information Science at the University of Pennsylvania. He received the Ph.D. degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology, with a minor in Physics, where his doctoral committee included George Verghese, Pablo Parrilo, and Devavrat Shah. He has held visiting positions at UC Berkeley, the Santa Fe Institute, and the Courant Institute of Mathematical Sciences at New York University, and was a postdoctoral researcher in the GRASP Laboratory at the University of Pennsylvania, working with Ali Jadbabaie.

Prof. Preciado is the recipient of the 2017 National Science Foundation CAREER Award and the 2018 IEEE Control Systems Magazine Best Paper Award. His work was also runner-up for the 2019 IEEE Transactions on Network Science and Engineering Best Paper Award, a finalist for the 2022 IEEE Robotics and Automation Society Best Paper Award in the Model-Based Optimization for Robotics Technical Committee, and received an honorable mention for the 2022 IEEE Transactions on Robotics Best Paper Award. He is a Senior Member of the IEEE and served as an Associate Editor for the IEEE Transactions on Network Science and Engineering and the IEEE Transactions on Control of Networked Systems.

His research lies at the intersection of network science, dynamical systems, control theory, optimization, and machine learning. His group develops mathematical and computational methods for the analysis, learning, and control of complex networked systems, with current interests including data-driven control, operator-theoretic methods, robust and safe learning, and the design of large-scale dynamical systems under uncertainty.

Note: From 2021–2025, I underwent treatment and recovery for leukemia. During this period, my professional activity was necessarily reduced. I have now completed treatment and fully recovered.