Sagnik Bhattacharya is a PhD candidate and graduate research assistant in electrical and computer engineering at the University of Maryland with a decade of research and teaching experience in information and coding theory. His work spans sampling, lossy compression, bandit learning, random field models, and quantum information theory, and includes developing single-shot bounds for universal sampling rate-distortion and studying shared information in Markov random fields. He has a strong theoretical background from IIT Kanpur and hands-on experience characterizing arbitrarily varying channels and the role of common randomness. As a teaching fellow he has taught engineering probability and communication systems, bridging deep theory with pedagogy. Colleagues describe him as a rigorous theorist who frequently turns abstract information-theoretic problems into tangible bounds and algorithms.
10 years of coding experience
Indian Institute of Technology Kanpur
Doctor of Philosophy - PhD, Electrical and Computer Engineering, Doctor of Philosophy - PhD, Electrical and Computer Engineering at University of Maryland
Primary, Secondary and Higher Secondary School, Primary, Secondary and Higher Secondary School at Apeejay School
Contributions:28 commits, 16 PRs, 31 pushes in 28 days
n-body-simulatorbodyn-bodysimulationsimulator
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.