Scientific Computing

Designing and optimizing high-performance computing solutions to solve complex scientific and engineering challenges with efficiency and scalability.

This site is still under construction. Drop by occasionally and stay tuned for updates.

Whether it’s large-scale simulations, data-driven models, or optimization of algorithms, I focus on leveraging the latest computing techniques to deliver efficient and scalable solutions to tackle complex problems that conventional methods can’t handle. This includes using distributed computing resources such as HPC clusters, GPU computing, or cloud-based architectures to handle massive datasets or computational workloads.

I ensure efficient and scalable solutions. My experience spans key programming languages such as Python, Julia, Rust, and Matlab, enabling computational efficiency across fields like renewable energy for system simulations, energy storage, or forecasting.
I integrate parallel computing techniques and ensure all software is scalable, maintainable, and optimized for evolving computational demands.