Computational chemist focused on molecular simulation, quantum-chemical analysis, and research software development.
My work uses computation to study chemically and biologically relevant systems, with particular interests in molecular dynamics, electronic-structure methods, soft matter, polymer and nanoparticle systems, and reproducible workflows for high-performance computing.
- Molecular dynamics simulations of complex chemical and biomolecular systems
- Polymer, nanoparticle, and ionic-liquid modeling
- TDDFT and quantum-chemical post-processing
- Scientific Python tools for chemistry and simulation analysis
- Reproducible HPC workflows for computational chemistry
- qctddft — A command-line toolkit for TDDFT post-processing from Q-Chem, including spectral analysis, region assignment, and clustering of representative structures.
- chemistry-analysis-tools — Python utilities for chemistry data handling, molecule-file cleanup, and partial-charge analysis.
- AmberMD-Scripting — Shell-based utilities for preparing and running AMBER molecular dynamics simulations.
I am especially interested in computational studies of chemically tunable soft-material systems, including polymers, nanoparticles, and ionic-liquid-containing environments, as well as in building practical tools that make simulation workflows more robust, transparent, and scalable.
Molecular simulation: GROMACS, AMBER
Quantum chemistry: Q-Chem, Gaussian, GAMESS, TDDFT
Analysis and scripting: Python, Bash, Pandas, Matplotlib, MDAnalysis
Computing: SLURM, Linux, workflow automation, reproducible HPC practice
I am interested in collaborations involving molecular simulation, mechanism-driven modeling, quantum-chemical analysis, simulation workflow design, and computational chemistry software.