I’m a Mathematical and Computational Modeler passionate about translating complex biological systems into data-driven insights. My research spans infectious disease modeling, drug dosing optimization, PK/PD modeling, systems biology, and public health analytics — combining mathematics, coding, and biology to drive healthcare innovations.
- Developed the first computational model to optimize oxytocin dosing regimens for improved maternal and neonatal outcomes (Python, R, MATLAB)
- 📌 Published in npj Women's Health
- Built COVID-19 transmission models for State Health Departments and UCLA COVID Behind Bars Project
- Developed Hawkes Process models to track COVID-19 spread in congregate settings (SciPy, Pandas)
- Assessed ring vaccination strategies and vaccine rollout optimizations
- Created ODE-based and multi-compartmental models for HBV/HDV kinetics and antiviral drug efficacy (MATLAB, Berkeley Madonna, Python)
- Modeled drug concentration vs. effectiveness (NONMEM, SciPy)
- Programming: Python | R | MATLAB |
- Modeling: ODE/PDE Systems | Stochastic Processes | PK/PD Modeling
- Libraries: SciPy | Pandas | NumPy | TensorFlow | PyTorch | Scikitlearn | Keras | API
- Data Analysis: R (ggplot2, dplyr) | SPSS | Berkeley Madonna
- Collaboration Tools: Jupyter Notebooks | Unix Shell | VS code
- Data Visualization: Matplotlib, Seaborn, Plotly
- Version Control: Git, GitHub
- 🧾 npj Women's Health: Mathematical modeling of genetic differences in oxytocin response
- 🧾 COVID-19 Modeling: Public health impact analysis (in collaboration with State Department of Public Health)
- 🧾 Multi-compartment HBV model: Parameter estimation and sensitivity analysis
🔍 I aim to bridge mathematical modeling, AI/ML, and healthcare innovation, contributing to precision medicine, drug development, and public health decision-making.
- 📧 Email: [email protected]
- 🔗 GitHub
- Google Scholar
⭐ GitHub Stats
✨ Open to collaborations in public health modeling, drug development, and AI/ML projects!