Statistical science is highly versatile and widely used in the real world as a tool for making decisions based on data. With that being said, there is room for debate regarding whether the analytical frameworks provided by existing statistical science are appropriate for specific analytical purposes.
I come from a background in theoretical physics, which is a discipline that elucidates the mechanisms behind phenomena and explores methods to control phenomena by leveraging those mechanisms. Investigating what happens statistically when data is gathered is also a form of studying mechanisms, and in this regard, it bears similarities to physics. Utilizing the perspective I developed through my research in theoretical physics, I aim to develop new data analysis frameworks that enable better interpretation and understanding of data.

[keywords]
Statistical Science ／ Multivariate Analysis ／ Causal Information Analysis ／ Machine Learning ／ Physics