Ayush Jain

Carnegie Mellon University, West Pomeranian University of Technology, Jain University, Nirma University

Papers

Total Citations

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About

Ayush Jain's research bridges robotics, artificial intelligence, and autonomous systems, with a focus on enabling intelligent machines to understand and interact with complex environments. His most impactful work introduces energy-based models as zero-shot planners for compositional scene rearrangement, demonstrating how robots can interpret compositional language instructions—such as multiple spatial relation constraints—to rearrange objects without task-specific training. This 2023 paper has garnered 16 citations for its novel approach to generalizing long and compositionally complex instructions. Jain's earlier foundational work includes hybrid path planning for mobile robots, integrating semantic, topological, and metrical layers from known environment models to produce efficient navigation strategies. He has also contributed to path tracing in holonomic drive systems, reducing overshoot through rotary encoder feedback, and explored AI-powered waste management, highlighting a progressive shift toward sustainable, intelligent waste handling. With a career spanning from low-level motion control to high-level semantic reasoning, Jain's research consistently pushes the boundaries of how robots perceive, plan, and act in the world, making him a notable figure in the advancement of embodied AI and autonomous navigation.