This is really abridged – please contact me for full and latest CV.
Education and experience
- Sep 2015 – Present, Postdoctoral fellow
Canadian Open Neuroscience Scholar
Rotman Research Institute, Baycrest Health Sciences,
Affiliated with University of Toronto, Toronto, ON, Canada.
- Sep 2014- Aug 2015, Research Scientist
Simon Fraser University, Vancouver, BC, Canada.
- Oct 2014 – Ph. D. in Engineering Science
Simon Fraser University, Canada
Thesis: Network-level imaging biomarkers for prognostic applications in neuroimaging
- May 2005 – M. Sc. in Physics
Indian Institute of Technology, Madras, India
Thesis: Infrared Thermography for Nondestructive evaluation of Material Defects.
- May 2003 – B.Sc in Mathematics, Physics and Computer science
Sri Venkateswara University, India
(University topper, with perfect score in Math).
Publications: google scholar
Invite talks and seminars (recent)
- June 2020, Talk on “Conquering confounds and covariates in machine learning and neuroscience”, at the Open Science Room at OHBM 2020, All virtual conference.
- June 2020, Tutorial on “Cross-validation: how to properly assess predictive performance“, at the OHBM 2020 Educational course on machine learning in Montreal, QC, Canada.
- Feb 2020, Workshop on “Optimization of preprocessing pipelines for functional MRI”, at the Rotman Research Institute, Toronto, ON, Canada.
- Feb 2020, Seminar on “Better decision support systems via quality, reproducible, and open science” at the Washington University in St. Louis (WashU), MO, USA.
- Jan 2020, Seminar on “Open neuroinformatics for better neurology research”, at University of Southern California (USC), Los Angeles, CA, USA.
- Nov 2019: Talk on “Better biomarkers via quality, reproducible, and open science” at the SickKids Research Institute, Toronto, ON, Canada.
- Oct 2019: Talk on “Better decision support systems via quality, reproducible, and open science” at University of Pittsburgh, Departments of Radiology and Psychiatry, Pittsburgh, PA, USA
- June 2019, Toronto: Compute Ontario Summer School, workshop on Machine in Learning in Neuroimaging, organized by SciNet at University of Toronto
- June 2019, Rome: Lead organizer and speaker at the Educational course on neuroimaging quality control at the OHBM 2019 in Rome
- Talk 1 on “Overview of Neuroimaging Quality Control (niQC), and introduction anatomical imaging QC“
- Talk 2 on “Tools and informatics for niQC“
- May 2019: Invited talk on “AI in Medicine: current insights and future challenges” at the University of Toronto Centre for Study of Pain seminar series
- Jan 2019: Co-instructor for the scientific communication workshop by the Research Training Centre at the Rotman Research Institute, Baycrest Health Sciences in Toronto
- Nov 2018: Seminar on “Why Python is ideal for [neuroscience] research software development?” at the Python Conference Canada (PyConCA).
- Sep 2018, Montreal: Workshop at the 2018 International Resting State and Brain Connectivity conference on practical introduction to machine learning: classifiers, feature selection, and cross-validation.
- June 2018, Singapore: Instructor at the OHBM 2018 educational course on Patter Recognition for Neuroimaging, teaching cross-validation. Testimonials: “Your lecture [on cross validation] solved all my problems with reviewers. Thank you so much!“
- May 2018, Ottawa: two of my neuroimaging tools were selected for presentation at the CANARiE’s Canadian Research Software Conference (CRSC’18) :
- Feb 2018: Canadian Partnership in Stroke and Recovery (CPSR) rounds at the Sunnybrook Research Institute on neuroinformatics and machine learning
- Feb 2018: Scientific communication workshop on “Translating Your Research For The Public:3-minute Thesis”, with Prof. Allison Sekuler, VP Research, Baycrest
- Jan 2018: Research Training Centre workshop at the Rotman Research Institute, Baycrest Health Sciences on “High Performance Computing” with detailed checklists and tips to build efficient workflows and effective cluster usage. [Slides]
- Jan 2018: Krembil Neuroimaging Rounds (University Health Network ) on machine learning, biomarker accuracy and best practices. [slides]
- Oct 2017: Canadian Biomarker Integration Network in Depression (CAN-BIND) lecture series on Network-level imaging biomarkers for prognostic applications.
- June 2017, Vancouver: Cross-validation primer at the OHBM Educational course on Pattern Recognition in Neuroimaging. Slides: here Mirror: here.
- May 2017: Research Training Centre workshop on “Practical Introduction to Machine learning”, at the Rotman Research Institute, Baycrest Health Sciences. Feedback: “an engaging and easy to follow presentation to an audience with no prior experience”
- Mar 2017: Dalla Lana School of Public Health, University of Toronto: Seminar on medical image analysis and machine learning.
- May 2016: Rotman Rounds at Rotman Research Institute, Baycrest: “Structural network analysis: Impact of network construction choices”
- Jan 2016: University of Sao Paulo, Brazil, Workshop on development of neuroimaging pipelines under the UoT-USP joint initiative in Neuroscience towards “Neuroinformatics Infrastructure For Collaborative Neuroimaging Research”
- Dec 2015: Krembil Research Institute Neuroimaging rounds on “Network-level morphometric features for prognostic applications in dementia”
- July 2015: Alzheimer Association International Conference (AAIC): Oral presentation on “Network-level analysis of PET metabolic features for detection of Alzheimer’s disease” in Washington, DC, USA
- Feb 2015: Coaching for Three Minute Thesis competition, titled: “Tips from Past Winners: coaching from the experts”