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About

Mohsen Sadeghi is a researcher at the intersection of motor control, human-robot interaction, and biomechanics, with a particular focus on how humans and robots manipulate complex, dynamically challenging objects. His most influential work, "Preparing to move: Setting initial conditions to simplify interactions with complex objects" (2021, 28 citations), reveals a remarkable insight into human dexterity: people strategically pre-configure their grip and posture before interacting with objects containing complex internal dynamics — such as a liquid-filled cup — effectively simplifying the control problem before it begins. This finding has significant implications for both understanding human motor planning and designing more capable robotic manipulators. Sadeghi has further explored how dynamic primitives and optimal feedback control underlie skilled object manipulation, and how multiple sensory modalities — including tactile feedback — contribute to real-time perception during complex interactions. His earlier work on sit-to-stand transfer using bio-inspired hierarchical control demonstrates a broader interest in adaptive, neurologically grounded movement planning. Collectively, Sadeghi's research bridges neuroscience and robotics, offering frameworks that help explain why even young children outperform state-of-the-art robots in everyday manipulation tasks.