CV

Jared Frazier

📧 jaredfrazierapplications [at] gmail [dot] com
💻 github.com/jfdev001

Experience

Research Software Engineer – Leibniz Institute of Atmospheric Physics (IAP)
October 2024 – Present

Automated and parallelized data-processing/visualization pipelines, reducing runtimes from 4 hours to minutes for terabyte-scale climate datasets on Linux HPC systems, decreasing per-job energy consumption and enabling potential cost savings of thousands of euros at scale.
Refactored and decoupled modules within a large-scale Fortran codebase (e.g., the ICON model), restructuring more than 10k lines-of-code into modular components, enabling separation of responsibilities and GPU porting efforts (PR).
Implemented significant build system and CI improvements in a leading open-source scientific machine learning library, reducing runtime by 50% and supported integration of PyTorch-based machine learning models into the ICON model (PRs).
Standardized internal development processes by introducing GitLab-based version control and deployed a lightweight GitLab runner on a Raspberry Pi to support static analyses (e.g., needs only seconds on production-grade HPC codebases with more than 500k lines-of-code) and internal automation workflows (blog).
Authored 5,000+ words of structured onboarding documentation covering HPC workflows, operational weather model compilation/debugging, Slurm scheduling, data management, Linux-based development practices, and led technical training on sustainable scientific software development.

M.Sc. Thesis: Discretization of Mechanical Metamaterials on Large-Scale Parallel Computers
Nov 2023 – Aug 2024

Co-developed distributed meshing algorithms for the simulation of metamaterials via finite element methods and domain decomposition methods.
See: GalerkinToolkit.jl

Intern: AI Engineer – National Institutes of Health
Jun 2022 – Aug 2022

Developed state-of-the-art computer vision models for tumour detection in CT scans using PyTorch and MMDetection.
Performed distributed model training on massive medical image datasets using NVIDIA A100 GPUs.
Authored a conference paper reporting improvements over state-of-the-art only 6 weeks after beginning the internship.

B.S. Thesis: Machine Learning in Atmospheric Science
Aug 2021 – Mar 2022

Implemented linear regression, random forest, LSTM/GRU RNNs, and CNNs for multi-step ambient temperature prediction on Mars using Curiosity Rover weather data.

NSF REU: Machine Learning in Drug Design – University of Michigan
Jun 2021 – Aug 2021

Implemented variational autoencoders for mapping discrete molecular representations to continuous representations.

Nano/Forensic Chemistry Research Assistant – MTSU
Jan 2019 – Aug 2020

Designed experiments and collected data using direct analysis in real time (DART) ambient ionization with mass spectrometry.
Authored two manuscripts and coauthored several others (see publications).

Free and Open-Source Software (FOSS) Contributions

FTorch | University of Cambridge: One of the most widely-used Fortran/PyTorch interoperability libraries

Designed and deployed GitHub Actions CI/CD pipelines for Intel oneAPI and GCC toolchains, expanding multi-compiler support and improving cross-platform build reliability (PRs).
Implemented automatic pkg-config file generation, simplifying library integration into legacy build systems (PR).
Enabled static library builds, allowing deployment in operational models where dynamic linking is restricted (PR).
Diagnosed and resolved subtle compilation issues, improving test-suite stability and build reproducibility (PRs).
Provided ongoing maintenance and community support (all PRs, all issues).

anemoi-datasets | European Centre for Medium Range Weather Forecasts: ML framework for advanced AI weather models

Refactored class-based dataset test suites into parametrized pytest workflows, improving test clarity and coverage (PR).
Replaced legacy testing patterns with modern pytest-native constructs, aligning test suite with current best practices (PR).
Migrated legacy Pydantic configuration models, contributing to Python 3.10+ / Pydantic v3 compatibility (PR).
Improved code correctness and maintainability by removing duplicated logic and simplifying error handling semantics (PRs).

Other Open-Source Contributions | Scientific computing projects in C, Fortran, and Julia

Ferrite.jl: Improved developer documentation and resolved broken links, enhancing library usability (PRs, issues).
PETSc: Corrected API documentation and tutorial examples for the world’s most widely used parallel numerical software library (PRs).
fftpack: Removed unused configuration logic (PR).
pFUnit: Identified and reported dependency edge-case failures affecting downstream HPC projects (issues).
SpeedyWeather.jl: Identified 5 reproducibility issues in documented examples, improving scientific correctness (issues).

Technical Skills

Programming Languages: Python, JavaScript/HTML/CSS, C++, C, Bash, Julia, Fortran
Libraries & Data Formats: FastAPI, SQLAlchemy, Pytest, NumPy, Pandas, Xarray, Eigen3, PyTorch, NetCDF, GRIB
Databases: SQLite
Artificial Intelligence: Pi, OpenCode, OpenClaude, MCP, Ollama, Agentic Workflows
Development Tools: Git, GitHub, GitHub Actions (CI/CD), GitLab, GitLab Runners (CI/CD), Docker
Build & Compile Tools: Make, CMake, GNU Autotools, GNU/Intel compilers, gdb, pdb, valgrind
HPC: Slurm, MPI, OpenMP, OpenACC
Operating Systems: Linux (e.g., Ubuntu LTS, RHEL), Windows

Languages

English (native), German (B1+**), Dutch (B1+**), Italian (A2**)

**Estimated CEFR Proficiency

Education

Master of Science (M.Sc.): Computational Science
University of Amsterdam (UvA) / Vrije Universiteit (VU)
2024

Bachelor of Science (B.S.): Computer Science
Middle Tennessee State University (MTSU)
2022

Publications

Frazier, J., Mathai, T.S., Liu, J., Paul, A., & Summers, R.M. (2023). SPIE Medical Imaging. doi: 10.1117/12.2655250.
Mahjour, B., Bench, J., Zhang, R., Frazier, J., & Cernak, T. (2023). RSC: Digital Discovery. doi: 10.1039/D3DD00008G.
Frazier, J., Cavey, K., Coil, S., Hamo, H., Zhang, M., & Van Patten, P. G. (2021). Langmuir, 37 (50), 14703-14712.
Tilluck, R., Mohan N., Hetherington, C., Leslie, C., Sourav, S., Frazier, J., et al. (2021). J. Phys. Chem. Lett., 12, 9677-9683.
Liang, J., Sun, J., Chen, P., Frazier, J., Benefield, V., & Zhang, M. (2021). Food Research International, 140, 109877.
Frazier, J., Benefield, V., & Zhang, M. (2020). Forensic Chemistry, 18, 100233.
Liang, J., Frazier, J., Benefield, V., Chong, N. S., & Zhang, M. (2019). Analytical Chemistry, 92(2), 1925–1933.

Conference Presentations

Frazier, J. (2021). Blue Mars Initiative: Developing Linear Regression and Artificial Neural Network Models to Forecast Mesoscale Martian Weather Conditions. National Council on Undergraduate Research (Virtual).
Frazier, J. (2020). Practical Investigation of Direct Analysis in Real Time Mass Spectrometry for Fast Screening of Explosives. Posters at the Capitol, Nashville, TN.
Frazier, J. (2019). Fast Screening of Explosives by Direct Analysis in Real Time Mass Spectrometry. 67th ASMS Conference, Atlanta, GA.

Key Graduate-Level Coursework

Uncertainty Quantification – 8.5/10
Bioinformatics I (Dynamical Systems modelling) – 8.5/10
Data Mining Techniques – 9/10
Programming Multi-Core & Many-Core Systems – 7.5/10
Parallel Programming Practical – 8.0/10
Numerical Algorithms – 8.5/10
Programming Large-Scale Parallel Systems – 8.5/10

Academic Honors and Awards

Amsterdam Merit Scholarship (2022 – 2024): The most prestigious merit scholarship at the University of Amsterdam, awarded to only 1–2 science master’s students outside EU/EEA each year.
Goldwater Scholarship (2020 – 2022): One of the most prestigious, nationally competitive U.S. scholarships supporting future leaders in natural sciences, engineering, and mathematics.
DAAD RISE Scholarship (2020, Canceled due to COVID-19): Research internship with Forschungszentrum Jülich / Helmholtz Institute for Renewable Energy (IEK-11).

Media Coverage

MTSU Alumni Spotlight (July 2025) An Atmosphere of Change – Feature on Involvement as Research Software Engineer at Leibniz Institute of Atmospheric Physics.
MTSU True Blue Mars Magazine Feature (July 2021) – Feature on Machine Learning Research for Martian Colonization.
MTSU Out of the Blue Interview – Blue Mars Initiative (July 2021) – Interview with VP for Marketing and Communications.
Goldwater Scholar Coverage by MTSU News & Rutherford Source (Apr 2020) – Local news coverage of Goldwater Scholarship Achievements.