Amol Pasarkar
Ph.D Candidate
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolAmol Pasarkar is a Ph.D. candidate at Columbia University with 10 years of experience building machine learning methods for neural data under the guidance of Liam Paninski. His background blends rigorous theoretical work—early research published in Innovations in Theoretical Computer Science with advisors Christos Papadimitriou and Mihalis Yannakakis—with hands-on engineering internships at Oak Ridge National Laboratory and PlaceIQ. Trained in computer science at Columbia, he focuses on translating statistical and computational theory into practical tools for neuroscience data analysis. Comfortable in both academic and applied settings, he brings experience across research, software engineering, and geospatial data from multidisciplinary teams. A detail that sets him apart is his trajectory from influential theoretical undergraduate research to targeted ML methods for neural datasets, signaling strength in both abstractions and real-world implementation.
11 years of coding experience
2 years of employment as a software developer
Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Columbia University in the City of New YorkFair Lawn High School
Github Skills (27)
vulkan10
visualization10
gpu10
scientific-visualization10
imaging9
rendering-engine9
webgpu8
matrix-decomposition8
segmentation7
shared-libraries7
jax7
jit6
neuroscience6
neuroimaging6
visual-recognition5
Programming languages (3)
Github contributions (5)
apasarkar/rlocalnmf
Jul 2022 - Jan 2025
New localNMF implementation with advanced background models and initialization options
Contributions:16 PRs, 130 pushes, 16 branches in 2 years 7 months
optionsbackground
apasarkar/jnormcorre
Apr 2022 - Jun 2025
Jax implementation of normcorre
Contributions:3 releases, 16 PRs, 102 pushes in 3 years 2 months
jax
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