Subhodh Kotekal
Norbert Wiener Fellow at Massachusetts Institute of Technology
Chicago, Illinois, United States
Summary
👤
Senior🎓
Top SchoolSubhodh Kotekal is a research scientist and Norbert Wiener Fellow at MIT who builds score-based generative AI and machine learning methods for detecting signals in extremely low signal-to-noise regimes where prediction is impossible. He holds a PhD in Statistics from the University of Chicago and has published at ICML, NeurIPS, IEEE Transactions on Information Theory, and the Annals of Statistics, reflecting a blend of theoretical rigor and practical algorithm design. His recent visiting research at Yale established statistical optimality results for diffusion models, showing he translates deep theory into concrete advances in generative sampling. With 11 years of experience spanning academic research and industry internships in high-scale data and systematic asset management, he combines probabilistic modeling, statistical decision theory, and scalable software implementation. Colleagues can expect work that emphasizes provable guarantees in frontier ML problems rather than engineering-by-heuristic.
10 years of coding experience
1 year of employment as a software developer
High School Diploma, High School Diploma at Kalamazoo Area Mathematics and Science Center (KAMSC)High School Diploma, High School Diploma at Portage Central High SchoolDoctor of Philosophy - PhD, Statistics, Doctor of Philosophy - PhD, Statistics at University of Chicago
Github Skills (17)
searchable8
fusion7
google-maps5
earth5
golang4
scraper4
api4
groupme3
maps3
discord2
backend2
discord-bot2
data-model1
visualization1
data-visualization1
Programming languages (2)
Github contributions (5)
uchicagotechteam/illinois-jobslink
Sep 2016 - Jan 2017
Contributions:61 commits, 16 PRs, 43 pushes in 3 months
apiillinoisscraperfront-endscraper-api
SKotekal/Pre_In_Post-Calculator
Jun 2015 - Jul 2016
Contributions:2 PRs, 5 pushes, 3 branches in 1 year 1 month
factorialexponentiationoutputstriginfix
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