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About

Soovadeep Bakshi is a robotics and automation researcher whose work centers on the planning, scheduling, and coordination of autonomous mobile robots (AMRs) in intelligent manufacturing environments. With a body of research spanning task scheduling, trajectory optimization, and risk-aware navigation, Bakshi has made meaningful contributions to one of the most pressing challenges in modern factory automation: deploying fleets of robots efficiently, safely, and sustainably. His most cited work, "Fast Scheduling of Autonomous Mobile Robots Under Task Space Constraints With Priorities" (2019, 17 citations), addresses the complex problem of optimally scheduling multiple AMRs under real-world constraints — a foundational challenge as robot deployments scale. Complementing this, his 2020 paper on energy-conscientious trajectory planning (14 citations) introduced energy efficiency as a central design criterion, reflecting growing industrial interest in sustainable automation. His 2021 contribution on risk-aware path planning (7 citations) pushed the field further by accounting for uncertain human-robot interactions, a critical concern in shared workspaces. Across his six notable publications, Bakshi demonstrates a consistent drive to bridge theoretical optimization — including quadratic programming and probabilistic methods — with practical deployment realities, making his research particularly valuable to students and engineers working at the frontier of smart manufacturing and autonomous systems.