Recent success in Deep Learning has attracted a lot of interest as well as investments for its applications in very diverse areas such as computer vision, robotics, financial technologies, cybersecurity, gaming and healthcare. In this lecture, I will formalize Deep Learning in the framework of geometry and surfaces in high dimensional spaces. This lecture will provide a non-traditional picture to Deep Learning that would potentially spawn new areas of research in Deep Learning.
Lee Hwee Kuan is the Head of the Imaging Informatics division in Bioinformatics Institute. Hwee Kuan also holds multiple concurrent positions as Principal Data Scientist in the Government Technology Agency of Singapore, Adjunct Associate Professorship in National University of Singapore and Principal Scientist position in the Singapore Eye Research Institute. His research involves using advanced computer vision, machine learning and mathematical models to build better machines; for the improvement of health care and discovery of biological knowledge. Hwee Kuan obtained his Ph.D. in Theoretical Physics from Carnegie Mellon University. He then held several postdoctoral positions in Oak Ridge National Laboratory, University of Georgia and Tokyo Metropolitan University. In 2006, he joined Bioinformatics Institute as a Principal Investigator in the Imaging Informatics Division.