Python developer with five years building numerical algorithms, statistical models, and research
software from scratch. Drawn to problems where mathematical analysis meets computational implementation.
Bethlehem, PA
Oct 2021 — Aug 2026
Graduate Researcher
Lehigh University
Developed computational models, numerical algorithms, and Python code studying how disorder, defects, and fractal lattices affect electronic properties of topological materials.
Wrote research software from scratch on general numerical libraries, producing tools reused across projects and by other group members.
Designed parameter sweeps and randomized simulations, and ran parallelized workloads on Linux HPC clusters using SLURM.
Built data workflows spanning parallel execution, HDF5/SQLite storage, and quantitative analysis, with an emphasis on accuracy and reproducibility.
Applied statistical modeling, regression, and neural-network classification to scientific datasets.
Authored and coauthored five peer-reviewed journal articles.
Aug 2021 — Jan 2023
Graduate Teaching Assistant
Lehigh University
Led undergraduate physics recitations and guided students through example problems.
Developed and administered quizzes, graded coursework and exams, and gave students feedback.
Education
PhD in PhysicsLehigh University · 2026
B.S. Physics, minor in MathematicsMoravian University · 2021
A.A. MathematicsNorthampton Community College · 2019
Publications
Five peer-reviewed journal articles, including sole- and shared-first-author work on topological materials, and a national conference presentation.
An open-source Python package for maximum-likelihood modeling of smooth, univariate, log-concave
probability distributions — including multimodal mixtures with automatic component selection,
bounded variables, and censored data.
pip install gibbus
Fits a single smooth analytic density instead of a piecewise or post-smoothed estimate.
Verifies every fit is log-concave everywhere, with tail-decay control so probabilities and quantiles stay accurate far into the tails.
Performance-critical code in Cython on top of NumPy and SciPy, with diagnostics and uncertainty estimates.
Documented public API, versioned model persistence, pytest suite, and cross-platform release builds via GitHub Actions.