For years, AI research has been measured by model accuracy. But for Dr. Trần, AI only becomes meaningful when it operates within real-world systems—where data is dynamic and value must be validated in practice.
Starting from a strong engineering foundation in Hanoi University of Science and Technology (Vietnam), he pursued his academic journey at Ritsumeikan University—one of Japan’s leading technology hubs. After completing his Master’s and PhD, he advanced his research career and is now an Associate Professor at Shiga University, while leading the Applied Physical AI Lab (APAI Lab)—an application-driven research environment.
His work focuses on Physical AI—moving beyond data-centric models toward systems that can interact with the real world. In this context, AI must not only process information but also observe, understand context, act, and solve measurable real-world problems.
His differentiation lies not only in academic credentials, but in approach:
- Not building AI to be “correct,” but to be usable
- Not separating research from business problems, but directly connecting them
- Not stopping at models, but building systems that can be deployed and scaled
In parallel, as CPO at Fabbi Holdings (Japan), he brings these research insights into real products—transforming AI into a scalable core capability for enterprises.
His journey reflects a broader shift in the AI era—where real-world deployment is no longer optional, but a strategic advantage.
