James Balamuta
Founder And Principal Consultant at HJJB, LLC
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJames Balamuta is a founder and principal consultant who blends 12 years of academic and industry experience to build production-ready ML systems with causal awareness for startups across the Bay Area and the Ozarks. He pairs a PhD in Informatics and award-winning research in state-space modeling and psychometrics with hands-on expertise in R, Python, Julia, C++, and GPU programming to deliver robust, interpretable models and scalable data pipelines. His work bridges theory and practice—augmenting traditional ML with causal inference and causal discovery methods to improve model reliability and business decisioning. An educator at heart, he has taught at UIUC and Stanford and has a track record of integrating industry tooling into curricula and high-performance computing workflows. Active in open source, he has contributed to notable projects like mlpack and Rcpp and to tooling around R builds and CI, reflecting a pragmatic focus on reproducibility and cross-language integration.
12 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (PhD), Informatics, Doctor of Philosophy (PhD), Informatics at University of Illinois Urbana-Champaign
Stackoverflow
20,416reputation
1.5mreached
276answers
25questions
fortran
top-5%
openmp
top-5%
r
top-1%
macos
top-5%
eigen
top-5%
hyperlink
top-5%
Github Skills (45)
c-language10
python10
r10
machine-learning10
travis-ci10
ruby10
pandoc10
build-automation10
autograd10
rcpp10
numerical-optimization10
macos10
cprogramming-language10
documentation10
optimizers9
Programming languages (23)
Github contributions (5)
mlpack/ensmallen
Jan 2019 - Nov 2020
A header-only C++ library for numerical optimization --
Role in this project:
Backend Developer
Backend DeveloperContributions:37 reviews, 30 commits, 14 PRs in 1 year 10 months
Contributions summary:James primarily contributed to code style improvements and bug fixes within the ensmallen library. Their work included adding newline characters to the end of files to address code style warnings, removing unused parameters, and correcting parameter initialization issues. They also incorporated release date information and made wording tweaks to documentation related to the CI process.
optimization-methodsoptimization-algorithmsnumerical-optimizationheader-onlycplusplus
PrairieLearn/PrairieLearn
Jan 2018 - Jan 2021
Online problem-driven learning system
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:76 reviews, 44 commits, 60 PRs in 3 years
Contributions summary:James contributed to the PrairieLearn system by implementing new features and modifying existing ones. Their work included adding R package installation capabilities and enhancing the `pl_checkbox` element. Further contributions involved improving the issue reporting system to show student names, refactoring and refactoring documentation, and fixing bugs. These efforts suggest a focus on improving both the functionality and user experience of the platform.
machine-learningproblemassessmentdrivingautograders
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