Ph.D. Candidate · Computational Scientist · Software Engineer
Building software at the intersection of science and engineering — from molecular simulations to AI-powered tools
I'm a Ph.D. candidate at The University of Texas at Austin, where my research focuses on computational modeling of molecular systems — building quantum mechanical models, running simulations, and writing software to extract meaning from complex scientific data.
Outside of academia, I build software that solves real problems: AI-powered job application tools, personal finance dashboards, and open-source Python packages for the scientific community.
Currently open to software engineering and data science roles.
| Project | Description | Stack |
|---|---|---|
| kairos | Turns a job description into a tailored, ATS-clean, advisor-reviewed CV PDF — without the AI-written smell | Claude Code HTML AI |
| Alprotein | Modular toolkit for excitonic Hamiltonians and optical spectra of molecular aggregates | Python NumPy SciPy |
| NeuralFinance | Neural network package for financial time-series analysis and prediction | Python PyTorch Pandas |
| publication-scripts | Reproducible analysis workflows and code supporting my peer-reviewed research papers | Python Jupyter |
| pdbtoolkits | Python toolkit for parsing and analyzing PDB protein structure files | Python Bioinformatics |
Languages
ML / Data Science
Scientific Computing
Tools & Cloud
The University of Texas at Austin — Ph.D. Candidate
Computational modeling of molecular aggregates, quantum mechanical simulations, optical spectra analysis
My research bridges quantum chemistry and software engineering — I write production-quality Python packages to model the physics of molecular systems, then validate them against experimental data.
See my publication scripts for reproducible code accompanying my papers.
Open to collaborations in scientific software, AI/ML, and data-driven research.