Neeloy Chakraborty
Papers
5
Total Citations
199
H-Index
2
About
Neeloy Chakraborty is a robotics researcher whose work centers on autonomous robot navigation, deep reinforcement learning, and human-robot interaction in complex, real-world environments. His research addresses one of mobile robotics' most pressing challenges: enabling robots to navigate safely and efficiently through dense human crowds under realistic, partially observable conditions. Chakraborty's most influential contribution, "Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning," has accumulated 118 citations since its 2021 publication, establishing a foundational framework for decentralized multi-agent navigation that relaxes prior assumptions about fully known agent dynamics. Building on this foundation, his 2023 paper on intention-aware navigation introduced attention-based interaction graphs to model diverse agent interactions and human intentions, garnering 76 citations and advancing the field's capacity to handle dense, interactive crowds. His most recent work, HEIGHT (2025), extends these contributions further by incorporating heterogeneous interaction graph transformers that simultaneously model spatial and temporal relationships among agents and static environmental constraints such as corridors and furniture. Together, Chakraborty's body of work — totaling nearly 200 citations — represents a coherent and progressive research agenda pushing robot crowd navigation toward greater safety, contextual awareness, and real-world applicability.
Research Focus
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