Greg Steeg

Associate Professor

Los Angeles, California, United States
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Summary

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Senior
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Top School
Greg Steeg is an associate professor and researcher with 11 years of experience bridging quantum information theory and machine learning, now based in Los Angeles. His work spans ambitious, foundational problems—from conserving information in curved spacetime and post-quantum entanglement to deriving causality from observational data and building interpretable unsupervised ML models. He has held research leadership roles at USC and the Information Sciences Institute and trained under John Preskill at Caltech, bringing deep theoretical rigor to applied research challenges. Known for exploring the "blessings of dimensionality," he combines mathematical physics insight with practical experimentation, including industry exposure at Google’s Machine Translation group.
code11 years of coding experience
job11 years of employment as a software developer
bookCalifornia Institute of Technology
bookB.S., Physics, Math, Philosophy, B.S., Physics, Math, Philosophy at Drake University
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Stackoverflow

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Github Skills (38)

covariance-matrix10
fenics10
preprocessing10
python10
toolbox10
machine-learning10
sampling10
manifold10
hierarchy10
factor-analysis10
representations10
information-theory10
parameter-estimation10
unsupervised-learning10
correlation10

Programming languages (1)

Python

Github contributions (5)

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gregversteeg/LinearSieve

Sep 2015 - Aug 2017

Contributions:24 commits, 8 pushes, 1 comment in 1 year 10 months
gregversteeg/NPEET

Oct 2014 - Oct 2022

Non-parametric Entropy Estimation Toolbox
Contributions:19 commits, 8 PRs, 12 pushes in 8 years 1 month
information-theoryentropypythonparametrictoolbox
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