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About

Subhasis Chaudhuri is a distinguished researcher whose work spans computer vision, image processing, robotics, and human-computer interaction. He is perhaps best known for his foundational contribution to computational imaging, particularly his 1999 book and research on *Depth From Defocus*, which pioneered a real aperture imaging approach to recovering three-dimensional scene structure from a single camera — a work that has garnered over 230 citations and remains a seminal reference in the field. His early research also extended into medical imaging, where he developed an automated retinal diagnosis system as far back as 1988, demonstrating a remarkably broad and forward-thinking research vision. Chaudhuri has made significant strides in robot learning and programming by demonstration, proposing innovative systems that enable robots to replicate human tasks by analyzing visual data captured during human performance. More recently, his work has evolved to address holistic 3D human-scene reconstruction from monocular imagery using adversarial learning, reflecting his engagement with cutting-edge deep learning methodologies. His exploration of haptic perception further underscores his multidisciplinary reach. Across three decades, Chaudhuri's contributions consistently bridge perception, intelligence, and embodied systems, making his work highly relevant to students pursuing computer vision, robotics, and AI.