Ryan Curtin
Primary Developer And Maintainer at mlpack
Atlanta, Georgia, United States
Summary
🤩
Rockstar🎓
Top SchoolRyan Curtin is a seasoned machine learning engineer and primary maintainer of the mlpack project, with 18 years of experience building high-performance, memory-efficient C++ libraries for real-world ML applications. Based in Atlanta, he architects and ships production-grade open-source tools—mlpack, ensmallen, and Armadillo—often tackling performance bottlenecks that others deem intractable. His work spans low-level algorithm design, numerical stability improvements, and cross-platform build automation, including substantial contributions to BinaryBuilder-based packaging for diverse OSes and architectures. Previously he developed accelerated in-database ML algorithms at RelationalAI and led applied research at Symantec, blending systems design with applied ML. He holds a PhD in Electrical and Computer Engineering from Georgia Tech and is known for preferring pragmatic, high-impact optimizations over theoretical complexity. A quirky aside: he describes himself as “stuck in an infinite breathing loop,” hinting at both persistence and a developer’s sense of humor.
18 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Electrical and Computer Engineering, Doctor of Philosophy - PhD, Electrical and Computer Engineering at Georgia Institute of Technology
Github Skills (23)
algorithm10
dependency-management10
algorithms10
c-language10
optimizers10
crossbuild10
machine-learning10
cmake10
optimisation10
mlpack10
build-automation10
neural-network10
cross-compiling10
cpp-templates10
cprogramming-language10
Programming languages (23)
Github contributions (5)
mlpack/ensmallen
Oct 2011 - Mar 2022
A header-only C++ library for numerical optimization --
Role in this project:
Back-end Developer
Back-end DeveloperContributions:38 releases, 171 reviews, 993 commits in 10 years 6 months
Contributions summary:Ryan's contributions primarily involved modifying and updating the core C++ library, specifically focusing on enhancing the optimization algorithms. They added and adjusted features related to parameter handling and performance optimization, refactoring some of the core code. These changes included improvements to line search, matrix calculations, and addressing potential issues related to numerical stability.
cppnumerical-optimizationoptimizationfunction-optimizationminimization
mlpack/mlpack
Jan 2010 - Jan 2023
mlpack: a fast, header-only C++ machine learning library
Role in this project:ML Engineer
ML EngineerContributions:33 releases, 1731 reviews, 7919 commits in 13 years 2 months
Contributions summary:Ryan made contributions focused on adapting the SoftmaxType to a new API by modifying and adding code to `softmax_impl.hpp`, `softmax.hpp`, `ann_layer_test.cpp`, and `serialization.hpp`. They also made modifications to adapt and re-enable Concat tests with various changes, including working with several matrix types and implementing modifications to support features such as multi-layer construction. Additionally, they worked to incorporate the `LinearRecurrent` layer and implemented BPTT.
cppmachine-learningmlpackmachine-learning-libraryc-plus-plus
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