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About

Shreeya Jain is an emerging robotics researcher whose work sits at the dynamic intersection of multi-robot collaboration, large language models (LLMs), and dexterous manipulation. She is perhaps best known for pioneering **RoCo: Dialectic Multi-Robot Collaboration with Large Language Models**, a groundbreaking framework that enables robots to engage in structured dialogue using pre-trained LLMs for both high-level strategic reasoning and low-level path planning — a paper that has garnered an impressive 123 citations and signals a paradigm shift in how autonomous robotic teams coordinate complex tasks. Beyond multi-robot systems, Jain has made meaningful contributions to robotic manipulation, notably through her work on heterogeneous bagging, where she developed generalizable strategies for placing diverse rigid and deformable objects into flexible containers — a notoriously difficult problem involving multi-body deformable interactions under limited observability. She has also explored human-robot interaction through a virtual reality teleoperation interface that allows users to asynchronously assign high-level assembly goals to remote robots using intuitive 6DoF object placement. Across her portfolio, Jain demonstrates a consistent commitment to making robot systems more capable, collaborative, and accessible — qualities that position her as a promising voice in next-generation robotics research.