Gaurav Bhalerao

Gaurav Bhalerao

University of Oxford


  • Neuroimaging
  • Magnetic Resonance Imaging
  • Machine Learning and Pattern Recognition
  • Computational Psychiatry
  • Brain Stimulation Modeling

My work

I am a postdoctoral researcher at the Wellcome Centre for Integrative Neuroimaging (WIN). My research interests include neuroimaging in psychiatry, machine learning, and computational modelling of brain stimulation.

I am currently working in the Dementias Platform UK (DPUK) project which aims to find news ways of detecting, treating and preventing dementia. My work involves adapting UK biobank brain imaging pipeline for various DPUK datasets that are made accessible through the DPUK Data portal to advance dementia research. This work also includes exploring the inclusion of additional pipelines for the calculation of measures specifically relevant to dementia cohorts and develop methods to facilitate cross-cohort analyses. Additionally, I will be working on making the pipeline accessible from the DPUK remote analysis environment for the users of the DPUK Data Portal that wish to apply the pipeline to new datasets.

I work with various neuroimaging software/tools for the analysis multimodal brain magnetic resonance imaging data such as FSL, SPM, Freesurfer, etc. I utilize various programming languages such as Python, MATLAB, R for coding, machine learning and statistical data analysis. I enjoy working with big data from various psychiatric cohorts, developing and troubleshooting brain imaging pipelines and reproducibility in neuroimaging research.

I have completed my Masters in Biomedical engineering at Manipal Institute of Technology (Manipal, India) and PhD in Dept of Psychiatry at National Institute of Mental Health and Neurosciences (NIMHANS, Bengaluru, India). For my PhD, I worked on developing machine learning classification models with the neuroimaging and eye tracking data for Schizophrenia and Obsessive Compulsive disorder. I also worked on developing computational brain models for studying the electric field distribution in the responders and non-responders of Transcranial direct current stimulation (tDCS) technique.

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