I am a computational neuroscientist with industry and academic research experience in neuroimaging and machine-learning. I am interested in development of robust biomarkers and machine-learning models for prognosis in neurodegenerative diseases. Currently I focus on development of neuroinformatic tools and implementation of reproducible computational workflows to assess and improve replication of imaging biomarkers and ML models. Concurrently, I am also involved in open-science and data harmonization projects relating to curation of diverse, open datasets representative of global populations.
At present, I am working with Dr. Jean-Baptiste Poline in the ORIGAMI lab at McGill University. I completed my PhD thesis on prognostic applications for Alzheimer’s disease using MR imaging and machine-learning techniques under Dr. Mallar Chakravarty at the University of Toronto. Subsequently, I worked as a researcher on a collaborative project between McGill and UMass universities assessing reproducibility of computational pipelines estimating cortical surfaces measures. I then went on to work at the Allen Institute, where I developed segmentation techniques and network spread models for quantifying cellular pathologies of Alzheimer’s disease in high-resolution microscopy data.
Within the larger research community, I am involved in multiple open-science and sustainable-neuroimaging initiatives. I develop and teach several “open” workshops (e.g. MAIN and educational courses. I am also a current treasurer for the Sustainability & Environmental Action SIG within the Organisation for Human Brain Mapping (OHBM) working on promoting sustainable research practices and conferencing.
Email: nikhil dot bhagwat at mcgill dot ca