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Argonne National Laboratory
Data Scientist
June 25, 2026 – Present
alcf4_benchmarks
February 2, 2024 – November 15, 2025
Repository for ALCF-4 Benchmarks as defined in the RFP.
View ProjectAI-for-science-hpc
August 14, 2023 – November 8, 2023
Supplemental material for "Demonstration of Portable Performance of Scientific Machine Learning on High Performance Computing Systems"
View Projectin-situ_ML
April 11, 2023 – April 20, 2023
Artifacts created for an SC23 paper submission on a framework for scalable in situ ML for CFD simulations
View ProjectlibCEED
December 6, 2017 – Present
CEED Library: Code for Efficient Extensible Discretizations
View ProjectCultural Fit Analysis
The candidate's projects show a strong focus on scientific computing, machine learning, and high-performance computing, which aligns well with research-oriented or data-intensive environments. The diversity of technologies used (Python, C++, Rust, Fortran, Jupyter Notebook) indicates adaptability and a broad technical curiosity. However, the projects are all personal, and there is only one current professional experience listed, which limits the assessment of collaborative work or enterprise-level contributions.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.