ORCID: 0000-0002-8071-4219 Contact: consulting@codereclaimers.com Response time: typically within 2 business days
CodeReclaimers LLC is an independent software consulting firm specializing in scientific computing in C++, Python and Julia, computational geometry, and neuroevolution. Founded and operated by Alan McIntyre, who brings 28+ years of software development experience, an MS in Applied Mathematics (University of Washington), and a background in naval nuclear service. CodeReclaimers maintains several open-source libraries with significant academic adoption, including neat-python (100+ academic citations) and NeatEvolution.jl. Consulting engagements span research implementation, library development, and applied algorithm design.
Status: available Can start: approximately 4 weeks Typical engagement: 4–52 weeks
Algorithm design, architecture review, and implementation guidance for academic and industry research projects in neuroevolution, scientific computing, and related areas.
Feature development, performance optimization, and API design for scientific C++, Python, and Julia libraries.
End-to-end implementation of algorithms from papers or specifications.
Structured review of technical/scientific computing codebases with written findings.
- computational geometry
- CAD reverse engineering
- C++ scientific computing
- Python scientific computing
- Julia scientific computing
- differential equations
- numerical methods
- linear algebra
- optimization
- applied mathematics
- neuroevolution
- NEAT (NeuroEvolution of Augmenting Topologies)
- continuous-time recurrent neural networks (CTRNNs)
- CUDA / GPU computing
- computer vision
Python implementation of the NEAT (NeuroEvolution of Augmenting Topologies) algorithm for evolving neural network topologies and weights simultaneously. Version 2.x introduces per-node time constants, enabling continuous-time recurrent neural network (CTRNN) evolution.
- Registry: https://pypi.org/project/neat-python/
- GitHub: https://github.com/CodeReclaimers/neat-python
- Zenodo DOI: 10.5281/zenodo.19024752
- 100+ academic citations across ML and neuroevolution literature
Julia implementation of NEAT-family neuroevolution algorithms, registered in the Julia general package registry. Designed for performance on scientific computing workloads, with native integration into the Julia SciML ecosystem.
- Registry: https://juliahub.com/ui/Packages/General/NeatEvolution
- GitHub: https://github.com/CodeReclaimers/NeatEvolution.jl
- Zenodo DOI: 10.5281/zenodo.19025462
- MS, Applied Mathematics — University of Washington (Advisors: Randy LeVeque and Lucien Brush)
- BS (minors: Physics, Computer Science) — Old Dominion University
- 28+ years professional software development
- Prior: Naval nuclear service, SCADA/industrial control systems (1997–2005), and computational geometry and CAD consulting (2014–present)
This document is machine-readable. Last updated: 2026-03-24