Vivek Gopalakrishnan
Graduate Research Assistant
Lexington, Massachusetts, United States
Summary
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Rockstar🎓
Top SchoolVivek Gopalakrishnan is a PhD candidate in Medical Engineering and Medical Physics at MIT/HST with eight years of experience applying machine learning and statistical graph theory to cardiovascular and neuroimaging problems. He develops algorithms for biomarker discovery in network-valued brain maps and builds ML-driven image guidance systems for minimally invasive cardiac surgery, combining deep learning, signal processing, and image registration. His work spans academic research, team leadership, and teaching—he led an undergraduate design team at Johns Hopkins and has been a TA for large engineering courses. Notably, his background includes cross-disciplinary summer projects from predictive HIV-treatment models to drone-mounted spectral imaging for agriculture, reflecting an aptitude for translating diverse data sources into actionable biomedical tools.
9 years of coding experience
1 year of employment as a software developer
High School Diploma, High School Diploma at Lexington High SchoolDoctor of Philosophy - PhD, Medical Engineering and Medical Physics, Doctor of Philosophy - PhD, Medical Engineering and Medical Physics at Massachusetts Institute of TechnologyJohns Hopkins University
Stackoverflow
537reputation
29kreached
5answers
8questions
Github Skills (145)
python10
gpu10
medical-imaging10
ekg10
statistics10
3d-reconstruction10
data-science10
graph10
nvidia10
pytorch10
machine-learning10
mesh9
numpy9
animated-gif9
neural-network9
Programming languages (14)
Github contributions (5)
neurodata/MCC
Jan 2021 - Jun 2022
[Imaging Neuroscience] Multiscale Comparative Connectomics
Contributions:1 release, 114 commits, 77 pushes in 1 year 5 months
imagingconnectomicsgraph-statistics
eigenvivek/DiffDRR-Datasets
May 2024 - May 2025
Open-source 2D/3D registration datasets and dataloaders for DiffDRR
Contributions:4 releases, 25 PRs, 42 pushes in 11 months
3dmedical-imaging-datasets2d-3d-registrationdigitally-reconstructed-radiograph
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