Prof. Shun-Ichi Amari
Life IEEE Fellow | Kyoto Prize Laureate 2025
Former Director, RIKEN Brain Science Institute (BSI), Japan
Pioneer of Information Geometry and Neural Networks
Prof. Shun-Ichi Amari is widely recognized as a pioneer in information geometry, neural networks, and theoretical machine learning. He is a Life IEEE Fellow, Kyoto Prize Laureate, Professor Emeritus of the University of Tokyo, and Honorary Science Advisor at RIKEN, Japan.
Prof. Amari has made fundamental contributions to the theoretical foundations of artificial intelligence, including neural network learning theory, natural gradient learning, blind source separation, self-organizing systems, and the development of information geometry as an interdisciplinary framework connecting differential geometry, statistics, and machine learning. His work has had a profound impact on modern artificial intelligence, deep learning, optimization theory, signal processing, and computational neuroscience.
Throughout his distinguished career, he served as Professor at the University of Tokyo and as former Director of the RIKEN Brain Science Institute. He has received numerous prestigious honors, including the IEEE Neural Networks Pioneer Award, the IEEE Emanuel R. Piore Award, the Japan Academy Prize, and the Kyoto Prize in Advanced Technology (2025). His pioneering contributions continue to shape the foundations of artificial intelligence and mathematical neuroscience worldwide.
Prof. Andrzej Cichocki
IEEE Fellow
Senior Visiting Researcher, RIKEN Center for Advanced Intelligence Project (AIP), Japan
Professor, Systems Research Institute, Polish Academy of Sciences, Poland
Prof. Andrzej Cichocki is a Polish electrical engineer and computer scientist recognized for his pioneering contributions to artificial intelligence, blind source separation, tensor networks, and brain-computer interfaces. He is a Full Professor at the Systems Research Institute of the Polish Academy of Sciences, a Professor at Nicolaus Copernicus University, and a Senior Visiting Researcher at RIKEN AIP, Japan.
His research focuses on machine learning, independent component analysis, non-negative matrix factorization, tensor decomposition methods, and biomedical signal processing, with applications in neuroscience and brain disease diagnosis. He has authored over 800 publications and is widely cited in computational intelligence and signal processing.
Prof. Cichocki is an IEEE Fellow (2013) and a Clarivate Highly Cited Researcher (2021–2023). He received an honorary doctorate from Nicolaus Copernicus University in 2017 and is internationally recognized for his contributions to modern machine learning and computational neuroscience.