Summary
Jorge Mendez-mendez is an Assistant Professor of Electrical and Computer Engineering at Stony Brook University with nine years of experience in lifelong and compositional machine learning for embodied agents. He completed a PhD at UPenn’s Lifelong Machine Learning Group and was a postdoc at MIT CSAIL, collaborating with leaders like Tomás Lozano-Pérez and Leslie Kaelbling on scalable learning systems. His research blends robotics, computer vision, and language to enable agents that accumulate, adapt, and recombine modular knowledge over their lifetimes. Jorge has interned at FAIR, MSR, and Facebook AI working on mixture-of-experts, compositional reinforcement learning, and multidomain dialog problems, bringing industry-scale perspectives to academic work. He studied and taught across Venezuela, Italy, and the U.S., and his background in electronics engineering informs a practical, systems-minded approach to algorithm design. Outside core research, he focuses on making complex lifelong learning problems tractable through modular decomposition that enables reuse and transfer.
9 years of coding experience
1 year of employment as a software developer
Bachelor of Engineering (B.E.), Summa Cum Laude, Electronics Engineering, Bachelor of Engineering (B.E.), Summa Cum Laude, Electronics Engineering at Universidad Simón Bolívar
Computer Science, Computer Science at Politecnico di Milano
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Pennsylvania
Spanish, English, Italian