He is for a Physics PhD with a strong background in computational materials science and data science. He holds dual Master's degrees in Physics and Electrical Engineering. His research expertise focuses on applying advanced computational methods to design and study novel materials for optoelectronic and quantum computing applications, including semiconductor heterostructures, graphene, and color centers in diamond. A key achievement involves successfully integrating atomic-scale and macroscopic-scale simulation codes to genetically design semiconductors with targeted properties. He has authored several peer-reviewed publications and possesses an IBM Data Science certification. With experience spanning academia and national labs (including NREL), he is also a dedicated educator, having taught physics and computational methods at the undergraduate level in both the US and France. He is proficient in Python, C/C++, and major data science libraries.