TATSUKI YAMAMOTO

I am currently pursuing a Master’s degree in human health sciences at the Graduate School of Medicine, Kyoto University.

During my undergraduate studies, I specialized in medical laboratory science and gained a solid understanding of clinical data and how it is generated.
This perspective—knowing not only what the data show, but also how they are obtained—forms a critical foundation for working with medical data.
Building on this foundation, I worked on developing a machine learning framework to model the time-course dynamics of patients’ internal states in fatal cancer, with the goal of better understanding cancer pathophysiology and advancing precision medicine.

Through this journey, I became fascinated by the potential of data science at the intersection of biology and medicine, and I moved into bioinformatics as a cutting-edge approach to understanding disease mechanisms and accelerating drug discovery.

Today, I am developing AI and machine learning methods to identify and prioritize drug target candidates.
Looking ahead, I aim to apply data science across a broader range of challenges in drug discovery—helping deliver new medicines to patients faster and at greater scale.