Joydeb Roychowdhury

Central Mechanical Engineering Research Institute

Papers

Total Citations

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About

Joydeb Roychowdhury is a pioneering researcher in tactile sensing and its real-world applications, with a particular focus on softness classification and agricultural automation. His work bridges robotics, machine learning, and sensor technology to solve practical challenges in minimally invasive surgery (MIS) and fruit and vegetable grading. Roychowdhury’s most-cited paper, "Tactile Sensing Based Softness Classification Using Machine Learning" (2014, 31 citations), demonstrates how robotic systems can distinguish material softness through tactile data, a critical capability for surgical precision and quality control in food processing. He further advanced this field with "Vegetable Grading Using Tactile Sensing and Machine Learning" (2014, 7 citations), which applies similar techniques to automate the sorting of produce by texture and ripeness, reducing reliance on manual inspection. By integrating machine learning algorithms with tactile sensor arrays, Roychowdhury has contributed to more intelligent, adaptive robotic systems capable of nuanced physical interaction. His work has been cited by researchers developing haptic feedback devices, agricultural robots, and medical simulators, underscoring its interdisciplinary impact. For students and researchers, Roychowdhury’s research exemplifies how tactile sensing can transform industries requiring delicate handling and precise material discrimination.