About me

I’m a multidisciplinary researcher and engineer with a strong foundation in chemical engineering, advanced mathematics, and artificial intelligence. My academic journey includes a degree in Chemical Engineering, a Master's in Mathematics and Computational Methods, another in Machine Learning, and a PhD spanning Computer Science and Chemical Engineering. This unique blend allows me to bridge theory with application, especially at the intersection of AI and the physical sciences.

Over the past six years, I’ve led and contributed to a wide range of machine learning projects—from predictive modeling and optimization to software development in high-stakes engineering environments. I’ve worked as a Machine Learning Engineer at Monolith AI and Syngenta, and collaborated with Imperial College London startups. During my PhD, I developed a software tool in the chemical engineering domain—valued at over $1 million—that integrates advanced ML and AI techniques to solve real-world industrial problems.

I'm a committed problem-solver, a savant-level programmer, and deeply passionate about using AI to drive breakthroughs in engineering, sustainability, and scientific discovery. Whether it’s building scalable ML systems, developing novel algorithms, or architecting end-to-end solutions, I bring both depth and creativity to every challenge.