Semanti Basu
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About
Semanti Basu is a rising researcher at the intersection of robotics, human-robot collaboration, and cognitive science. Her work centers on enabling robots to reason and act intelligently under uncertainty by leveraging human-like causal models of the physical world. In her highly cited 2025 paper, “Robot Planning Under Uncertainty for Object Assembly and Troubleshooting Using Human Causal Models,” Basu demonstrates how even imperfect human mental models can be integrated into a robot’s decision-making framework. This allows collaborative robots to make smarter, more adaptive choices during complex tasks like object assembly and troubleshooting, especially when information is incomplete. By bridging the gap between human intuition and machine planning, her research addresses a fundamental challenge in robotics: how to make robots not just precise, but also context-aware and collaborative. With her work already garnering attention in the field, Basu is contributing to a future where robots can work alongside humans more naturally, learning from our understanding of how things fit together—and what happens when they don’t.
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