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Seshagopalan Thorapalli Muralidharan is a pioneering researcher in soft robotics, focusing on the design, modeling, and control of compliant robotic systems. His work centers on developing bio-inspired robots that leverage soft, tendon-driven actuators to achieve safer and more adaptable movement than traditional rigid robots. A key contribution is the synthesis of optimal gaits for quadruped robots using deep reinforcement learning, a breakthrough that enables soft-legged robots to traverse complex terrains with unprecedented efficiency. His most-cited paper (45 citations) demonstrates this by combining soft continuum actuators with machine learning to generate stable, energy-efficient locomotion. Muralidharan also contributed to the design of a soft robotic eye actuator for the social robot HARU, emphasizing safety in human-robot interactions, particularly with children, in compliance with UN standards. His comprehensive survey on design optimization for compliant and soft robotics (7 citations) provides a systematic framework for the field, categorizing manufacturing, actuation, and application trends. Through these contributions, Muralidharan is advancing the frontier of safe, adaptive robotics, bridging the gap between theoretical design and real-world deployment in social and exploratory contexts.