Technical skills acquired through experience, research, and continuous learning.

I build robust data pipelines and analytical frameworks for large, complex, multi‑dimensional datasets. From spatio‑temporal data wrangling to extracting actionable insights, I’m adept at manipulating and analyzing multi‑variable data to reveal hidden patterns and support data‑driven decisions.

I specialize in building and optimizing deterministic data‑model frameworks, leveraging advanced sensitivity analysis methods — including Monte Carlo simulations — to refine predictive performance. I routinely design, scale, and run parallelized modeling experiments on high‑performance computing platforms to tackle complex, data‑intensive challenges.

Developing robust pipelines and best practices for organizing, storing, and sharing complex environmental datasets — stay tuned!

Work in progress — actively building expertise in machine learning and large language models. Skilled at designing deep learning neural networks with TensorFlow Keras for multivariate time series predictions, aiming to unlock smarter data insights and powerful automation.

I use Python daily to build robust models and perform in-depth data analysis with powerful libraries like NumPy, Pandas, and Scikit-learn. I’m skilled at turning complex datasets into clear, insightful visualizations using Matplotlib, helping to uncover trends and communicate results effectively.

I write efficient code in R, Fortran, C, and MATLAB, adapting to whatever the project demands. I’m also skilled at translating code between languages to streamline workflows and integrate diverse tools seamlessly.