Computational chemist working across molecular simulation, electronic-structure methods, and scientific computing.
I develop and apply molecular modeling methods to study chemically and biologically relevant systems, with work spanning molecular dynamics, free-energy calculations, QM/MM, DFT/TDDFT, soft matter, polymers, nanoparticles, and biomolecular systems. Alongside the science, I build Python and Bash tools and reproducible HPC workflows for simulation setup, analysis, and research data processing.
- Molecular dynamics of complex chemical and biomolecular systems
- Free-energy and mechanistic molecular modeling
- QM/MM, DFT/TDDFT, and quantum-chemical analysis
- Polymer, nanoparticle, and ionic-liquid modeling
- Scientific Python tools for simulation and chemistry workflows
- Reproducible, scalable workflows for high-performance computing
- qctddft — Tested Python command-line toolkit for Q-Chem TDDFT post-processing, including spectrum generation, spectral-region assignment, and structural clustering. The project uses packaged installation,
pytest, and GitHub Actions CI. - chemistry-analysis-tools — Lightweight computational-chemistry utilities for molecular-file handling, partial-charge analysis, and molecular-simulation trajectory analysis.
- AmberMD-Scripting — Bash utilities for preparing and running staged AMBER molecular-dynamics workflows.
- Polymer/nanoparticle research workflows — Ongoing tools for PLGA model preparation, nanoparticle construction, quality control, provenance, simulation handoff, and trajectory analysis. Research-sensitive source and production data remain private while related work is in preparation.
Molecular simulation: GROMACS, AMBER, molecular dynamics, free-energy calculations
Quantum chemistry: Q-Chem, Gaussian, GAMESS, DFT/TDDFT, QM/MM
Scientific software: Python, Bash, NumPy, pandas, Matplotlib, MDAnalysis, pytest, Git, GitHub Actions
Computing: Linux, SLURM, GPU/HPC workflows, workflow automation, reproducible research computing
I am particularly interested in problems where mechanistic molecular modeling, rigorous computation, and scientific software can contribute to molecular design, drug discovery, biomolecular research, or soft-materials science.
- 🌐 Personal site
- 🧾 Google Scholar
- 🔬 ORCID