My main research interest is to pursue computational principles in the visual cortex of the primate brain from theoretical point of view. In particular, my questions regard how the intermediate to higher visual areas in the ventral stream process and represent complex visual features such as shapes and objects. My theoretical approach is to use machine learning theories for formalizing the neural visual representations and the cortical bidirectional visual processing in terms of statistical learning and Bayesian inference of visual stimuli. My research explicitly relates such theories with the computation in the actual brain, through comparison and analysis of various neural data, in collaboration with phyisiology experimentalists. Also, for understanding of the complex higher vision, I consider it important to have a mutual inspiration with the contemporary artificial intelligence techniques, which has led to my recent contributions to the deep learning research.
I have been enjoying since my childhoold playing European classical music with the piano. My recent favorites are French modern pieces, especially, Debussy and Ravel.
Here are some of my performances on YouTube.
I won a few prizes at competitions:
Many people are astonished, but I'm originally from "hard-core" computer science. I used to work on applying discrete mathematics such as automata, logic, and type theory to the design and implementation of novel programming languages in the direction of helping programmers in safety, productivity, and efficiency. My main target in this research direction was to use theory of tree automata to the design of type-safe programming languages specialized to processing XML data. The project ended in 2010.
Foundations of XML Processing: The Tree-automata approach (Cambridge University Press)
"... the process of acceptance will pass through the usual four stages:
--- J.B.S. Haldane (1963)