Pablo A. Parrilo

Pablo A. Parrilo is the Joseph F. and Nancy P. Keithley Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT). He serves as Associate Director of the Laboratory for Information and Decision Systems (LIDS) and maintains affiliations with the Operations Research Center (ORC), as well as connections to multiple research centers including the Simons Institute programs in Geometry of Polynomials and Bridging Continuous and Discrete Optimization. His extensive academic journey includes previous positions as Assistant Professor at ETH Zurich's Automatic Control Laboratory and Visiting Associate Professor at Caltech, with research visits to UC Santa Barbara, Lund Institute of Technology, and UC Berkeley.

Parrilo received his Electronics Engineering undergraduate degree from the University of Buenos Aires and earned his PhD in Control and Dynamical Systems from the California Institute of Technology. His foundational education in engineering and dynamical systems established the basis for his subsequent research contributions in optimization and control theory.

Professor Parrilo's research spans optimization methods for engineering applications, control and identification of uncertain complex systems, robustness analysis and synthesis, and the development of computational tools based on convex optimization and algorithmic algebra. His work bridges theoretical mathematics with practical engineering problems, particularly through sum of squares (SOS) optimization techniques. He has pioneered applications in semidefinite programming, algebraic geometry, and polynomial optimization, creating powerful frameworks for solving challenging non-convex problems. His influential SOSTOOLS MATLAB toolbox has become a standard resource for researchers working in sum of squares optimization.

Analysis of his recent publications reveals a consistent focus on advancing convex optimization techniques, with particular emphasis on sum of squares methods, graph-based optimization, and applications to robotics and control systems. His work increasingly integrates algebraic geometry with optimization theory, developing novel approaches for polynomial optimization problems and exploring connections between continuous and discrete optimization paradigms. Recent publications demonstrate growing interest in robotics applications, particularly in motion planning and manipulation through convex relaxations.

Among his notable distinctions are the Finmeccanica Career Development Chair, the Donald P. Eckman Award from the American Automatic Control Council, the SIAM Activity Group on Control and Systems Theory Prize, the IEEE Antonio Ruberti Young Researcher Prize, the Farkas Prize from the INFORMS Optimization Society, and recognition as an IEEE Fellow. These awards reflect his significant contributions to optimization theory, control systems, and their applications across multiple disciplines.

Professor Parrilo has advised numerous PhD students and postdoctoral researchers who have gone on to prominent positions in academia and industry. His research has been supported by multiple National Science Foundation grants, including the AF "Algebraic Proof Systems, Convexity, and Algorithms" project and the FRG "Semidefinite Optimization and Convex Algebraic Geometry" project. He has organized influential workshops and programs that have shaped research directions in optimization and control theory.

Within MIT, Parrilo leads a vibrant research group focused on optimization theory and applications, working closely with the Laboratory for Information and Decision Systems. His group develops both theoretical foundations and practical computational tools, maintaining strong connections with researchers across mathematics, computer science, and engineering disciplines. The group's work on SOSTOOLS and other software packages has created valuable resources for the broader optimization community.