Takanori Adachi

Takanori Adachi received his MSc from Tokyo Institute of Technology in 1982. His major at TITech was theoretical computer science and foundation of mathematics, especially domain theory of the lambda calculus. After spending another three years at the doctoral course in TITech, he started his own company of software development in 1985. He implemented the first C++ compiler that works on Japanese workstations, and wrote Japan's first C++ book in 1988. In the meantime, he took part in the ISO/ANSI C++ standardization committee. The C++ string library he designed here was adopted as part of the C++ standard library and is currently used on almost every single computer.
In 1997, he transferred to Morgan Stanley, an investment bank in Wall Street, and started an algorithmic trading business. He designed a strategy-description language, implemented a robot to interpret instructions written in that language, and traded with it against stock exchanges in a full-automatic fashion. He also managed funds using a high-frequency index-arbitrage strategy written in this language in the markets of New York, Tokyo, London and Frankfurt.
After the collapse of the Lehman crisis, he returned to Tokyo from New York and enrolled in Graduate School of International Corporate Strategy at Hitotsubashi University in order to study mathematical finance. He received his PhD in Management in 2014 with a dissertation entitled "Considerations on Filtrations and Ambiguity in Mathematical Finance".
After that, he joined Department of Mathematical Sciences, Ritsumeikan University as a visiting professor. In April 2018, he was appointed to the post of professor at Graduate School of Management, Tokyo Metropolitan University.

There are two projects in his recently focused research.
One is to apply categorical probability theory to finance theory. In fact, the theory of categorical probability began with his recent paper "a category of probability spaces" which is an evolutionary version of his research on "monetary risk measures" analyzed from a category-theoretical point of view. He is currently trying to apply this theory to stochastic control theory, especially in time-inconsistent cases.
Another project is to build a rigorous mathematical theory on algorithmic trading. This is an attempt to provide a mathematical foundation for understanding the events that he experienced at Wall Street, and to forecast the future wave of AI-driven trading. In this connection, he is also interested in theoretical foundations of machine learning using probability theory.

His style of research and education is to keep facing to various problems by focusing on "what problems do practitioners really want to solve and how can academia contribute to solving these problems?" or conversely, "to promote people's happiness, what kind of goal should be set by academia so that its results are returned to society?", based on his twenty-five years' experience as a practitioner.