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About

Somya Goyal is a researcher whose work bridges the critical domains of humanoid robotics, flexible sensor technology, and deep learning for industrial automation. Her most impactful contributions center on developing robust control systems for bipedal locomotion, specifically through her pioneering work on push recovery for humanoid robots in dynamic environments. This research, which has garnered a combined 17 citations, addresses the fundamental challenge of maintaining balance—a key enabler for real-world deployment of humanoid robots. Goyal’s approach not only generates control systems but also incorporates data classification using K-Means clustering, demonstrating a unique integration of machine learning with mechanical control. Expanding her expertise, she has also contributed to the development of flexible piezoresistive pressure sensors based on ionic membranes, a technology with promising applications in wearable healthcare, artificial skin, and soft robotics. Looking forward, her recent work on deep learning architectures for industrial automation and robotics, published in 2025, highlights her forward-looking perspective on how AI can drive efficiency and autonomous operation in manufacturing. Through this diverse portfolio, Goyal is establishing herself as a versatile researcher advancing both the hardware and intelligence of next-generation robotic systems.