Mayukh Das

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About

Mayukh Das is a researcher at the intersection of artificial intelligence, natural language processing, and robotics, with a focus on developing agents capable of communication, learning, and problem-solving in grounded environments. His most-cited work, "Towards Problem Solving Agents that Communicate and Learn" (2017, 9 citations), co-authored with a team including Sriraam Natarajan and Dan Roth, addresses the challenge of building AI systems that can understand language, reason about tasks, and interact with physical or simulated worlds. This paper, presented at the First Workshop on Language Grounding for Robotics, exemplifies his contribution to bridging symbolic reasoning with machine learning for embodied agents. Das’s research emphasizes integrating language grounding with decision-making, enabling agents to learn from instructions and adapt through interaction. While his citation count reflects a focused, emerging impact, his work is notable for its interdisciplinary approach, combining insights from NLP, robotics, and reinforcement learning. For students and researchers, Das’s efforts highlight the critical step toward creating AI that can communicate naturally and act intelligently in real-world settings—a foundational challenge in modern AI research.