Rahul Biswas
Postdoctoral Researcher at University of California, San Francisco
United States
Summary
👤
Senior🎓
Top SchoolRahul Biswas is a Postdoctoral Scholar at UCSF with nine years of experience bridging statistical theory, machine learning, and computational neurology to infer causal brain networks from neural time series. He earned a PhD in Electrical & Computer Engineering from the University of Washington, where his doctoral work produced novel causal inference methods applied to benchmarks, mouse models, and human Alzheimer’s data. Rahul has a strong foundation in statistics from the Indian Statistical Institute and has tackled diverse research problems—from detecting stellar substructures to seizure onset detection and epidemiological pattern clustering—demonstrating versatility across domains. He founded Kaneva Consulting to translate his research-driven approaches into applied solutions, signaling an entrepreneurial bent alongside academic rigor. Known for combining principled probabilistic modeling with practical validation on biological datasets, he often focuses on methods that remain robust in high-dimensional, low-sample regimes. Colleagues value him for turning complex theoretical ideas into reproducible analyses that impact both neuroscience research and applied consulting projects.
9 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD, Electrical and Computer Engineering, Doctor of Philosophy - PhD, Electrical and Computer Engineering at University of WashingtonMaster's degree, Statistics, Master's degree, Statistics at Indian Statistical Institute, Kolkata
Github Skills (8)
probabilistic-graphical-models10
causal-discovery10
causal-inference10
python9
graph9
time-series8
signal3
pypi1
Programming languages (2)
Github contributions (5)
biswasr/TimeAwarePC
Dec 2023 - May 2025
A python package for finding causal functional connectivity from neural time series observations.
Contributions:10 releases, 26 pushes, 10 tags in 1 year 4 months
shlizee/TimeAwarePC
Apr 2022 - Jan 2023
A python package for finding causal functional connectivity from neural time series observations.
Contributions:3 releases, 232 commits, 4 PRs in 9 months
pythontime-seriescausal-modelstimeseriescausal-discovery
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.