Arundhati Banerjee

Papers

Total Citations

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About

Arundhati Banerjee is a robotics and artificial intelligence researcher whose work centers on autonomous systems, multi-agent coordination, and probabilistic decision-making. Her research tackles the challenging problem of active search — enabling teams of autonomous robots to efficiently locate sparse targets, such as gas leaks, radiation sources, or disaster survivors, in unknown environments. Across her notable publications, including "Decentralized Multi-Agent Active Search for Sparse Signals" (2021), "Asynchronous Multi Agent Active Search" (2020), and "Multi-Agent Active Search using Detection and Location Uncertainty" (2023), Banerjee has made meaningful contributions to how multiple aerial robots collaborate under real-world constraints such as asynchronous operation and compounded sensing uncertainties. Her work addresses both detection uncertainty and localization uncertainty, pushing the boundaries of what adaptive decision-making algorithms can achieve in dynamic, unstructured settings. Each of her key papers has garnered citations within the research community, reflecting growing interest in scalable, decentralized approaches to search-and-rescue and environmental monitoring missions. For students exploring autonomous robotics or multi-agent systems, Banerjee's research offers a rigorous and practically motivated foundation at the intersection of probabilistic reasoning, active learning, and real-world robot deployment.