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ECE Seminar Series – Nov 14 (Fri) @ 2:00 PM: "A Tutorial on Graphs of Convex Sets: A New Optimization Framework for Robotics and Control," Tobia Marcucci, Asst. Prof., ECE, UCSB

Date and Time
photo of tobia marcucci

Location: Engineering Science Building (ESB), Room 1001
Come at 1:30p for Cookies, Coffee and Conversation
LECTURE at the ECE SEMINAR SERIES

 

Abstract

In this talk, I will give a high-level tutorial on graphs of convex sets, with emphasis on their applications in robotics, control, and, more broadly, decision making. Mathematically, a Graph of Convex Sets (GCS) is a graph in which vertices are associated with convex optimization problems and edges couple pairs of these problems through additional convex costs and constraints. Classical problems defined over ordinary weighted graphs (such as the shortest path, the traveling salesman, and the minimum spanning tree) naturally generalize to a GCS, giving rise to a rich class of problems at the interface of combinatorial and convex optimization. I will first discuss how GCS problems can be solved efficiently, and then show how they naturally encompass multiple core problems in robotics and control. Finally, I will present GCSOPT, an open-source and easy-to-use Python library that enables solving real-world GCS problems in just a few lines of code.

Bio

Tobia Marcucci is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara (UCSB). He is also affiliated with the Department of Mechanical Engineering and the Center for Control, Dynamical Systems, and Computation (CCDC) at UCSB. Before joining UCSB, he was a Postdoctoral Scientist at Amazon Robotics. He received a PhD in Computer Science from the Massachusetts Institute of Technology (MIT), under the supervision of Russ Tedrake and Pablo Parrilo. During his PhD, he also spent one year at Stanford University visiting Stephen Boyd’s group. His doctoral dissertation was awarded the 2025 MIT EECS George M. Sprowls Thesis Award in Artificial Intelligence and Decision Making. He holds a Bachelor’s and a Master’s degree (cum laude) in Mechanical Engineering from the University of Pisa. His research lies at the intersection of convex and combinatorial optimization, with applications to robotics, motion planning, and optimal control.

Hosted by: Lecture at the ECE Seminar Series

Submitted by: Tobia Marcucci <marcucci@ucsb.edu>