About

USA Citizen - Residence Japan - Wedded - Pythagoras (711) fan.

4th Generation American - Family from Italy / Germany / Austria

DOB: 10/10. Blood Type 0. 188cm tall.

Born: Silicon Valley, California

I publish under the name of JD Michelin focusing on AI Fintech and Risk Management.

Current research is on an algorithm what I call "Bermuda Swaptions".

Early Life and Education

Michelin grew up in Silicon Valley, California and developed an early interest in technology, economics, and systems thinking. He was raised Catholic and graduated from a private Catholic High School. He studied Environmental Engineering at Portland University and later completed graduate-level coursework in finance at Harvard Graduate School of Arts and Sciences (GSAS). He also pursued studies in computer science through coursework associated with the University of California, Berkeley, while continuing independent research in central bank policies and interest rates.

Career

Michelin became involved in blockchain technology during its formative years and was an early participant in the Bitcoin ecosystem. Beginning in 2014, he worked with Bitcoin mining operations and the sale of blockchain-related products, contributing to the adoption of cryptocurrency technologies during a period of rapid industry growth.

His professional focus later expanded into artificial intelligence and fintech, where he has concentrated on forecasting market volatility, risk management methodologies, and the application of machine learning to financial decision-making. He has also been involved in e-commerce and technology ventures, combining insights from software development, finance, and digital infrastructure.

Research and Interests

A central theme of Michelin's work is the study of trends, cycles, and predictive systems. He has expressed particular interest in identifying emerging technological and financial developments before they become widely recognized. His research philosophy emphasizes clarity, simplicity, and the use of current information, summarized by his principle that "research should be fresh, simple, and clear."

In addition to fintech and artificial intelligence, Michelin maintains interests in comparative religion, esoteric traditions, and the history of financial forecasting. Observers have noted parallels between his approach to market analysis and the cyclical methodologies associated with Euclid and Pi.

Michelin's current research focuses on the application of numerical fractals, cyclical structures, and pattern-recognition techniques to financial forecasting. His work explores how recurring mathematical relationships may influence market behavior, volatility, and long-term economic cycles. Drawing from fields including quantitative finance, artificial intelligence, and historical market analysis, Michelin investigates whether fractal-based models can improve risk management and forecasting accuracy across financial markets.

His research emphasizes the integration of machine learning with cycle analysis and numerical pattern detection, seeking practical methods for identifying emerging trends and potential turning points in complex financial systems.

Personal Life

Michelin has traveled to more than 30 countries and cites international travel as an important influence on his perspective. Outside of his professional activities, he enjoys surfing, snowboarding, and visiting theme parks, particularly Universal Studios Japan and volunteering at Red Cross Society.

Despite his involvement in rapidly evolving technological sectors, Michelin has emphasized the importance of humility, generosity, and lifelong learning. He is motivated by developing forecasts and testing their accuracy against future outcomes, viewing prediction as both a practical discipline and a continuing intellectual challenge.