
Computational astrophysicist, 15+ yr in Python, C++/C, FORTRAN, MATLAB, a little Java, a tiny bit of HPC. I’m disabled. He/him
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
temp
September 30, 2023 – September 30, 2023
some temp data to just put on the web so I can get it
View ProjectDigitalFractorAlgorithmSimulationCPP
August 12, 2017 – December 31, 2020
My C++ research on a simulation of a digital fractional order circuit device in Visual C++ (Windows XP)
View ProjectPythonNumericalAndStatisticalErrorAnalysis
June 9, 2017 – December 31, 2020
Python and bash scripts using the output of the Fortran code to use the exponential convergence of the Discontinuous Galerkin error to extrapolate to the infinite order value, then sum over multipole modes to obtain the self force in an extreme mass ratio black hole binary inspiral, modeled using a scalar effective source. My python code analyzing output from the Fortran code.
View ProjectprototypeLIGOEventTriggerHBasedatabase
September 14, 2016 – December 31, 2020
HBase database intended for LIGO data written in Java
View ProjectBHrayTracingImageMPIpython
April 18, 2016 – December 31, 2020
LSU computational physics 2 final project
View ProjectCPP-General-Relativity-wave-equation-simulation
February 7, 2015 – November 8, 2025
Numerical Relativity computation of a black hole binary inspiral in the extreme mass ratio limit. Scalar approximation, Schwarzchild background. Self-force, effective source. Currently broken and not under development. Requires a private library anyway.
View ProjectDG1D-Fortran-test
February 5, 2015 – November 8, 2025
Fortran code written to compare the output of Peter's code to the new C++ code. Based on Peter Diener's discontinuous Galerkin 1D code for a scalar field around a Schwartschield BH with hyperbolical slicing in Fortran.
View ProjectCultural Fit Analysis
The candidate's projects are predominantly personal and research-oriented, focusing on computational physics and numerical simulations. While this demonstrates intellectual curiosity and deep technical interest, there is limited evidence of experience in team environments, diverse project types, or direct application of data science in a business context. The projects are highly academic, which might require an adjustment to a more industry-focused data science culture. The target role 'Data Scientist' is partially aligned with the candidate's strong numerical and analytical background, but the specific focus on physics simulations rather than typical data science applications (e.g., predictive modeling, machine learning, A/B testing) suggests a potential gap in cultural fit for a standard industry data science role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong focus on independent research and complex problem-solving. However, there is no direct information regarding collaboration, communication, or other soft skills. The operational fit for a Data Scientist role is moderate, given the strong technical foundation in relevant areas, but the lack of explicit experience in data pipelines, machine learning frameworks, or business-oriented data science applications is a gap.