Dr. Subodh Raj is an Assistant Professor (Senior Grade) in the Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, and a member of the Robotics and Automation Thrust Area Group. His research interests span computer vision, machine learning, robotics, and intelligent sensing, with a focus on developing reliable, explainable, and resource-efficient vision-based intelligent systems. His current research focuses on vision-based intelligent robotics, explainable and uncertainty-aware artificial intelligence, human pose and activity understanding, biometric recognition, and edge AI and embedded intelligence.
He received his Ph.D. in Electronics and Communication Engineering from the National Institute of Technology Calicut. His doctoral thesis, “From Recovery to Recognition: Analysis of Human Poses, Actions, and Activities”, explored computational approaches to human pose, action, and activity analysis using low-rank and tensor-based modelling, subspace learning, and deep learning techniques. This research established the foundation for his continued work in human-centred computer vision and intelligent perception.
Dr. Subodh has professional experience spanning academia, industry, and international research. He previously served as a Senior Researcher at the Norwegian University of Science and Technology (NTNU), Norway, where he contributed to research on biometric recognition, particularly iris and face recognition, with an emphasis on biometric image quality assessment, explainability, and robust recognition systems. He has also worked as an AI/ML Computational Science Specialist in industry, contributing to the development of scalable AI and machine learning solutions, including cloud-based AI systems.
In addition to his research activities, Dr. Subodh is actively involved in teaching, student mentoring, curriculum development, and academic initiatives across electronics, embedded systems, machine learning, computer vision, and robotics. He serves as a reviewer for several journals and conferences in computer vision, pattern recognition, and machine learning. He is also a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).
His research aims to bridge theoretical advances and practical applications by developing intelligent systems that are reliable, interpretable, and suitable for real-world deployment, with particular emphasis on human-centered perception, intelligent robotics, and resource-aware AI.