Krishna Prasad Miyapuram

Associate Professor, Cognitive Science

Research Areas : Neuroeconomics & Neuromarketing, Computational Cognitive Science, Neuroimaging (EEG, fMRI) & Brain Computer Interface, Machine Learning & Artificial Intelligence.

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My research integrates the cognitive processes of learning and decision making mechanisms in humans. Ongoing projects include behavioral and neural correlates of statistical learning, perceptual and value-based decision making. A wide range of experimental and analytic techniques such as psychophysics, eye tracking, brain imaging methodologies (EEG, fMRI) and computational modelling (Reinforcement learning, Bayesian approaches) are used. With machine learning approaches applied to structural MRI images, I am working on early detection of Alzheimer's’ disease.


B.Sc: Osmania University, 1998

M.Sc: University of Hyderabad, 2000

MTech: University of Hyderabad, 2004

PhD: University of Cambridge, U.K., 2008

Professional and Teaching Experience

Associate Professor, Indian Institute of Technology, Gandhinagar, (Feb 2020 to Present)

Assistant Professor, Indian Institute of Technology, Gandhinagar, (Oct 2012 to Feb 2020)

Postdoctoral Fellow, Center for Mind/Brain Sciences, University of Trento, Italy (July 2011 - Sept 2012)

Cognitive Psychologist, Unilever R&D, The Netherlands (Aug 2008 - Jan 2011)

Visiting Researcher, Core Research for Evolutionary Science & Technology, Kyoto, Japan (July - Sept 2003)

Visiting Researcher, Exploratory Research for Advanced Technology, Kyoto, Japan (Dec 2000 - Feb 2001)

Research Assistant, Indo-Japanese project, University of Hyderabad (Aug 2000 - July 2002)

Research work


  • Dhananjay Sonawane, Krishna Miyapuram, Derek Lomas, Bharatesh Rs, GuessTheMusic: Song Identification from Electroencephalography response, CODS-COMAD 2021
  • Raunak Swarnkar, Krishna Miyapuram. EEG Correlates of Effector-Specific Representation during Visuo-Motor Sequence Learning, ICONIP 2020
  • Pandey, P., & Miyapuram, K. P. (2020, July). Classifying Oscillatory Signatures of Expert vs NonExpert Meditators. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-7). IEEE.
  • Tripathi, R., Mukhopadhyay, D., Singh, C. K., Miyapuram, K. P., & Jolad, S. (2019, December). Characterization of functional brain networks and emotional centers using the complex networks techniques. In International Conference on Complex Networks and Their Applications (pp. 854-867). Springer, Cham.
  • Goyal, S., & Miyapuram, K. P. (2019). Feedback influences discriminability and attractiveness components of probability weighting in descriptive choice under risk. Frontiers in psychology, 10, 962.
  • Chawla, M., & Miyapuram, K. P. (2018). Context-Sensitive Computational Mechanisms of Decision Making. Journal of Experimental Neuroscience.
  • Nath, S. S., Mukhopadhyay, D., & Miyapuram, K. P. (2019, January). Emotive Stimuli-triggered Participant-based Clustering Using a Novel Split-and-Merge Algorithm. In Proceedings of the ACM India Joint International Conference on Data Science and Management of Data (pp. 277-280). ACM.
  • Tripathi, R., Mukhopadhyay, D., Singh, C. K., Miyapuram, K. P., & Jolad, S. (2018). Characterizing functional brain networks and emotional centers based on Rasa theory of Indian aesthetics. arXiv preprint arXiv:1809.05336.
  • Viraj Mavani, Shanmuganathan Raman, Krishna P. Miyapuram:
    Facial Expression Recognition Using Visual Saliency and Deep Learning. ICCV Workshops 2017: 2783-2788
  • Chawla, M., & Miyapuram, K. P. (2016, September). Common neural coding across domains of decision making identified by meta-analysis. In Front. Neuroinform. Conference Abstract: Neuroinformatics.
  • Devu Mahesan, Manisha Chawla, Krishna P. Miyapuram:
    The Effect of Reward Information on Perceptual Decision-Making. ICONIP (4) 2016: 156-163
  • Goyal, S., Miyapuram, K. P., & Lahiri, U. (2015, November). Predicting Consumer's Behavior Using Eye Tracking Data. In Soft Computing and Machine Intelligence (ISCMI), 2015 Second International Conference on (pp. 126-129). IEEE.
  • Manisha Chawla, Krishna P. Miyapuram:
    Influence of Previous Choice and Outcome in a Two-Alternative Decision-Making Task.ICONIP (2) 2015: 467-474
  • M. Chawla, and K.P. Miyapuram, Comparison of meta-analysis approaches for neuroimaging studies of reward processing: A case study. IJCNN 2015: 1-5 {Talk}
  • Miyapuram, K.P., Pamnani, U., Doya, K., Bapi, R.S. Inter Subject Correlation of Brain Activity  during Visuo-Motor Sequence Learning, 21st International Conference on Neural Information Processing (ICONIP2014).
  • Neeraj Kumar, Jaison A. Manjaly, K.P. Miyapuram. (2014) Feedback about Action Performed can Alter the Sense of Self Agency, Frontiers in Psychology (Consciousness Research), 5:145.
  • E.H. Zandstra, K.P. Miyapuram, P.N. Tobler. (2013). Understanding consumer decisions using behavioural economics. Progress in Brain Research, 202:197-211.
  • K.P. Miyapuram, V.S.C. Pammi.  (2013). Understanding Decision Neuroscience – A multidisciplinary perspective and neural substrates. Progress in Brain Research, 202:239-66.
  • K.P. Miyapuram, P.N. Tobler, L. Gregorios-Pippas, W. Schultz. (2012) BOLD responses in reward regions to hypothetical and imaginary monetary rewards. NeuroImage 59(2):1692-1699.
  • V.S.C. Pammi*, K.P. Miyapuram*, Ahmed, K. Samejima, R.S. Bapi, K. Doya. (2012). Changing the Structure of Complex Visuo-motor Sequences Selectively Activates the Fronto-Parietal Network. NeuroImage 59(2):1180-1189. {* = Equal contribution}
  • R.S. Bapi, K.P. Miyapuram, F.X. Graydon, K. Doya. (2006). fMRI investigation of cortical and subcortical networks in the learning of abstract and effector-specific representations of motor sequences. NeuroImage, 32(2):714-727. {Editor’s Choice Award for the year 2006}


  • Principal Investigator, Statistical Learning of Category Information: A neuroimaging Investigation, DST Cognitive Science Research Initiative, 2013-2016
  • Principal Investigator, Integration of Perceptual and Value based decision making: A Cognitive and Computational Approach, DST Cognitive Science Research Initiative, 2015-2017.
  • Mentor, The Relevance of 9th Rasa In The Generation Of Aesthetic Delight: A Neuroaesthetic Approach Using EEG and Eye Tracking, DST Cognitive Science Research Initiative, Postdoctoral fellowship to Dr. Dyutiman Mukhopadhyay, 2014-2016.
  • Principal Investigator, Deep Learning of Musical Experience using EEG, PlayPowerLabs, USA, 2019-2020
  • Principal Investigator, Early detection of Alzheimer’s using Individualized Brain Atlases and Machine Learning in multilateral project on Brain functional connectivity in health and disease - under India-Trento Programme for Advanced Research, DST, 2019-2022