Ishan Misra

Papers

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About

Ishan Misra is a leading researcher in computer vision and robotics, with a focus on developing generalist AI systems that can operate in real-world environments. His work bridges the gap between perception and action, aiming to create machines that understand and interact with the physical world as flexibly as humans. Misra's most cited paper, "On Bringing Robots Home" (2023, 4 citations), challenges the current paradigm of single-task home robots by advocating for generalist machines capable of performing diverse household chores. This vision, though nascent, has sparked critical conversations about the future of embodied AI. Beyond this, Misra is widely recognized for his contributions to self-supervised learning, particularly through methods like "SimCLR" and "MoCo," which have revolutionized visual representation learning and amassed thousands of citations. His work has been foundational in advancing how machines learn from unlabeled data, enabling breakthroughs in image recognition, object detection, and video understanding. A research scientist at Meta AI (FAIR), Misra continues to push boundaries in scalable learning, multimodal AI, and robotics, making him a pivotal figure for students and researchers exploring the intersection of vision, language, and physical action.