John Eric Steephen

Dr. John Eric Steephen studied Electronics Engineering at College of Engineering Trivandrum, and Biomedical Engineering for his Master’s degree at IIT Bombay. After obtaining his PhD in Computational Neuroscience from IIT Bombay, he made a transition to Cognitive Science and Experimental Psychology during his post-doctoral positions at the Centre for Neural and Cognitive Sciences, University of Hyderabad and Kohli Centre on Intelligent Systems, IIIT Hyderabad. He was a recipient of the DST-CSRI post-doctoral fellowship twice. Prior to pursuing his Master’s degree, he worked as a software engineer in the IT industry in India and Germany.

He joined IIITM-K in 2019 as an Assistant Professor and shifted to Digital University Kerala subsequently. He teaches mainly courses on programming, data structures and database management for the post-graduate programs of the University. He is the co-ordinator of the CAN Lab at Digital University Kerala. The CAN Lab, under the School of Digital Sciences, conducts research and development in the areas of Cognitive Science, Assistive & Biomedical technologies, and Neurocomputing. He has published papers in the areas of affective computing, computational neuroscience and experimental psychology in internationally well-respected journals. He is currently the Principal Investigator of a K-DISC funded medical research project and the Mentor of a DST funded neuroscience research project. He is also a reviewer of manuscripts for publishers such as Elsevier, Hindawi, Wiley and Springer Nature.

His research interests over the years have spanned the areas of biomedical engineering, computational neuroscience, affective computing and experimental psychology. These can be broadly divided into the following themes:

• Gain an improved understanding of the normal and abnormal functioning of CNS neurons using computational models and suggest methods and techniques for more effective treatment of addiction and other mental disorders.
• Study the human emotion system employing computational methods and techniques, supported by experiments, to contribute towards a better understanding of emotional disorders and thus assist mental health specialists in treating and managing them optimally.
• Develop computational emotion models and emotion dynamics simulators that have potential applications in surveillance systems, human-computer interaction, robotics, games, virtual reality training and anywhere affectively intelligent systems are required.
• Research and development of simple medical and assistive devices with an objective to prevent and manage various medical conditions, with special focus on devices that can address problems that are unique to resource-constrained settings.