Ayan Chakrabarti

Toyota Technological Institute at Chicago, Washington University in St. Louis

Papers

Total Citations

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About

Ayan Chakrabarti is a researcher working at the intersection of robotics, autonomous systems, and machine learning, with a focus on solving fundamental challenges in robot navigation and design. His work addresses critical problems in environments where traditional localization methods fall short, particularly developing intelligent approaches to beacon-based positioning systems when GPS is unavailable. His most-cited contribution, "Jointly Optimizing Placement and Inference for Beacon-based Localization" (2017, accumulating 10 citations across versions), demonstrates his interest in co-optimizing system components simultaneously rather than treating them as isolated problems — a hallmark of his research philosophy. This theme extends into his 2019 work on deep reinforcement learning, where he tackled the compelling challenge of jointly learning robot physical design and motion control policies, recognizing that hardware and software are fundamentally inseparable in real-world robotics applications. With 15 total citations across his key works, Chakrabarti's research appeals to both the robotics and machine learning communities. His contributions are particularly valuable for students interested in how principled joint optimization frameworks can unlock new capabilities in autonomous systems operating under real-world constraints.