Minh Ha Quang

Dr. Minh Ha Quang serves as a unit leader at RIKEN Center for Advanced Intelligence Project (RIKEN-AIP) in Tokyo, Japan, where he directs the Functional Analytic Learning Unit. Previously, he worked as a researcher at the Italian Institute of Technology in Genova, Italy.

He earned his PhD in Mathematics from Brown University (Rhode Island, USA) under the supervision of renowned mathematician Stephen Smale. His doctoral research established the foundation for his current work at the intersection of advanced mathematics and machine learning.

Dr. Ha Quang specializes in applying functional analytic and geometrical frameworks to machine learning challenges. His research focuses on generalizing information geometry and optimal transport distances from finite-dimensional to infinite-dimensional Gaussian measures and processes. This work explores dimension-independent convergence properties and sample complexity through the interplay of reproducing kernel Hilbert spaces, Gaussian processes, and geometric frameworks. His theoretical formulations yield computationally efficient closed-form expressions with practical applications.

As leader of the Functional Analytic Learning Unit at RIKEN-AIP, Dr. Ha Quang oversees research that bridges deep mathematical theory with contemporary machine learning methodologies. His team investigates how geometric and functional analytic approaches can enhance understanding of complex data structures and improve computational efficiency in statistical learning applications.