Prof. Shun-ichi Amari (Professor-Emeritus at the University of Tokyo, Senior Advisor of the RIKEN Brain Science Institute (BSI))

Title

Statistical Neurodynamics of Deep Learning

Biography

Shun-ichi Amari was born in Tokyo, Japan, on January 3, 1936. He graduated from the Graduate School of the University of Tokyo in 1963 majoring in mathematical engineering and received Degree of Dr. of Engineering. He worked as an Associate Professor at Kyushu University and the University of Tokyo, and then a full professor at the University of Tokyo, and is now Professor-Emeritus. He moved to RIKEN Brain Science Institute and served as Director for 5 years and is now Senior Advisor. He has been engaged in research in wide areas of mathematical science and engineering, such as topological network theory, differential geometry of continuum mechanics, pattern recognition, and information sciences. In particular, he has devoted himself to mathematical foundations of neural networks, including statistical neurodynamics, dynamical theory of neural fields, associative memory, self-organization, and general learning theory. Another main subject of his research is information geometry initiated by himself, which applies modern differential geometry to statistical inference, information theory, control theory, stochastic reasoning, and neural networks, providing a new powerful method to information sciences and probability theory. Dr. Amari is past President of International Neural Networks Society (INNS) and Institute of Electronic, Information and Communication Engineers (IEICE), Japan. He received Emanuel A. Piore Award and Neural Networks Pioneer Award from the IEEE, the Japan Academy Award, C&C Award, INNS Gabor Award and Caianiello Memorial Award. He was founding co-editor-in-chief of Neural Networks, and is serving on the editorial boards of many other journals. Professor Shun-ichi Amari is IEEE Life Fellow, foreign member of Polish Academy of Science, and Professor-Emeritus at the University of Tokyo. He has published more than 300 papers, including initiation of information geometry and pioneering works on neural networks.

Prof. Karlheinz Brandenburg (Senior Professor(emeritus) at Technische Universität Ilmenau, CEO of Brandenburg Labs)

Title

Creating Auditory Illusions with Binaural Technology: Algorithms and Test Methodology

Biography

Karlheinz Brandenburg received the Dipl.-Ing. and Dipl.-Math. degrees in electrical engineering and mathematics and the Dr.-Ing. degree in electrical engineering from the Friedrich-Alexander-Universität, Erlangen-Nürnberg, Erlangen, Germany, in 1980, 1982, and 1989, respectively. He is currently Senior Professor (emeritus) at Technische Universität Ilmenau, Germany and CEO of Brandenburg Labs, a startup company specializing in immersive audio technologies. Following times as a Postdoctoral Member of Technical Staff at AT&T Bell Laboratories in Murray Hill, U.S.A. and again Friedrich-Alexander-Universität he joined the Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany, as head of the Audio and Multimedia Department. He is the founding director of the Fraunhofer-Institut für Digitale Medientechnologie (Fraunhofer IDMT), Ilmenau where he retired in July, 2019. For his pioneering work in digital audio coding (as a main contributor to the mp3 and AAC audio coding standards), perceptual measurement techniques, wave field synthesis, psychoacoustics, and analysis of audio and video signals he received many awards. Among them are the Cross of the Order of Merit of the Federal Republic of Germany, the IEEE Masaru Ibuka Consumer Electronics Award, the German Future Award (shared with his colleagues), and the Audio Engineering Society Silver Medal Award. Furthermore, he is a member of the Hall of Fame of the Internet Society and the IEEE Consumer Electronics Association. He received honorary doctorate degrees from the Universities Koblenz-Landau, Germany, Leuphana University of Lüneburg, Germany and Universitat Politechnica de Valencia, Spain.

Prof. Min Wu (Professor and Distinguished Scholar-Teacher at University of Maryland)

Title

When Signal Forensics Meets Public Health

Biography

Min Wu is a Professor of Electrical and Computer Engineering and a Distinguished Scholar-Teacher at the University of Maryland, College Park. She is currently serving as Associate Dean of Engineering for Graduate Affairs. She received the B.E. degree in electrical engineering -- automation and the B.A. degree in economics from Tsinghua University, Beijing, China, in 1996 with the highest honors, and her Ph.D. degree in electrical engineering from Princeton University in 2001. At UMD, she leads the Media, Analytics, and Security Team (MAST), with main research interests on information security and forensics, multimedia signal processing, and applications of data science and machine learning for health and IoT. Dr. Wu was elected as IEEE Fellow, AAAS Fellow, and Fellow of the National Academy of Inventors. She chaired the IEEE Technical Committee on Information Forensics and Security, and served as Vice President - Finance of the IEEE Signal Processing Society and Editor-in-Chief of the IEEE Signal Processing Magazine. She was a founding member of APSIPA and elected to serve on the Board of Governors of APSIPA (2019-2021). She has been elected to serve as President-Elect (2022-2023) of the IEEE Signal Processing Society.
[URL: http://www.ece.umd.edu/~minwu/]