Bartolomeo Stellato
Bartolomeo Stellato is an optimization researcher whose work connects machine learning with real-time decisions in robotics and other dynamic systems. He coauthored OSQP, a solver for convex quadratic programs, in a 2017 preprint; the paper appeared in Mathematical Programming Computation in 2020. After a postdoctoral appointment at MIT's Sloan School of Management and Operations Research Center, he joined Princeton's ORFE faculty in 2020 and received an NSF CAREER Award in 2023. His work with Rajiv Sambharya, Georgina Hall, and Brandon Amos earned an honorable mention for the 2026 INFORMS Computing Society Prize, and he received a Sloan Research Fellowship in 2026. He is an assistant professor at Princeton, where he works on mathematical optimization, machine learning, and optimal control with applications in robotics.
- Now at
- Princeton University
- Works
- 70
- Citations
- 2,771
- h-index
- 19
Publication numbers from OpenAlex, as of 27 October 2026.
Timeline
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2017–2020
A solver for quadratic programs
He coauthors a 2017 paper introducing OSQP, an operator-splitting solver for convex quadratic programs, with Goran Banjac, Paul Goulart, Alberto Bemporad, and Stephen Boyd. Their paper appears in Mathematical Programming Computation in 2020.
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2020
Joining Princeton's ORFE faculty
He joins Princeton's Operations Research and Financial Engineering faculty in 2020 after a postdoctoral appointment at MIT's Sloan School of Management and Operations Research Center. His training includes a DPhil in Engineering Science from Oxford, an MSc in Robotics, Systems and Control from ETH Zürich, and a BSc in Automation Engineering from Politecnico di Milano.
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2023
An NSF CAREER Award
He receives the NSF CAREER Award in 2023. His research develops data-driven tools for fast decisions in uncertain settings, with applications in robotics, autonomous systems, and power systems.
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2026
An INFORMS honorable mention
With Rajiv Sambharya, Georgina Hall, and Brandon Amos, he receives an honorable mention for the 2026 INFORMS Computing Society Prize. Their work uses data-driven methods to speed parametric convex optimization while retaining convergence and performance guarantees.
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2026
A Sloan Research Fellowship
He receives a Sloan Research Fellowship in 2026. His research develops algorithms for fast and accurate real-time decisions, including drone navigation, power-grid dispatch, and financial trading.
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As of October 2026
Assistant professor at Princeton
As of October 2026, he is an assistant professor of Operations Research and Financial Engineering at Princeton. His research spans data-driven computational tools for mathematical optimization, machine learning, and optimal control, with applications in autonomous systems, data science, and robotics.
Career
- Since 2020Princeton UniversityAssistant professor
- Massachusetts Institute of TechnologyPostdoctoral researcher
Education
- University of OxfordDPhil in Engineering Science
- ETH ZurichMSc in Robotics, Systems and Control
- Polytechnic University of MilanBSc in Automation Engineering
Sources and credits
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- OSQP: An Operator Splitting Solver for Quadratic Programs
- Publications | Bartolomeo Stellato
- Junior faculty awards recognize outstanding teaching and research
- FDS Colloquium: Bartolomeo Stellato (Princeton), Data-Driven Perspectives on First-Order Methods for Convex Optimization
- ICS Prize 2022-2026 - Computing Society
- Four from Engineering win Sloan Fellowships - Princeton Engineering
- Bartolomeo Stellato - Princeton Engineering

