Max Simchowitz
Max Simchowitz is an assistant professor in the Machine Learning Department at Carnegie Mellon University with a courtesy appointment in the Robotics Institute. He received his PhD from UC Berkeley in 2021 under Ben Recht and Michael Jordan, and completed postdoctoral research with Russ Tedrake at MIT. His research focuses on theoretical foundations and methodologies for machine learning problems with interactive, sequential, or dynamical components, particularly reinforcement learning and robot learning. His work has been recognized with an ICML 2018 Best Paper Award, an ICML 2022 Outstanding Paper Award, and best paper finalist designations at RSS 2023 and ICRA 2024.
“we propose an alternative approach in which computationally intensive VLM queries are made during train-time to learn a lightweight latent memory that can be efficiently queried at deployment time.”
Source→“Max Simchowitz co-developed the project direction, architecture, experimental design, and played a significant role in paper writing”
Source→“Max Simchowitz - Lab/Institution: Carnegie Mellon University (CMU Maxlab) - Co-senior author with equal advising”
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