My contributions to the scientific community spanning optical science, machine learning, and interdisciplinary research.
We present a novel machine learning approach for real-time correction of atmospheric turbulence in large ground-based telescopes, achieving 78% reduction in alignment time.
Deep learning pipeline for automated analysis of fluorescence spectroscopy data in biomedical applications, improving accuracy by 45% over traditional methods.
An ethnographic study on how cultural perspectives influence scientific collaboration, based on research conducted at Waseda University, Tokyo.
Examining modern approaches to optical science education and the integration of machine learning concepts in undergraduate curricula.