John E. Hopcroft is the IBM Professor of Engineering and Applied Mathematics in Computer Science at Cornell University. His research centers on theoretical aspects of computer science. He was dean of Cornell’s College of Engineering from 1994 to 2001.
In 1992 he was appointed by President George H.W. Bush to the National Science Board, which oversees the National Science Foundation, and served through May 1998. He serves on Microsoft’s Technical Advisory Board for Research Asia, and the advisory boards of IIIT Delhi and Seattle University’s College of Engineering.
He is a member of the National Academy of Engineering (1989) and National Academy of Sciences (2009), and a fellow of the American Academy of Arts and Sciences, American Association for the Advancement of Science, Institute of Electrical and Electronics Engineers (IEEE), Association of Computing Machinery (ACM), and Society of Industrial and Applied Mathematics.
He has received the A.M. Turing Award (1986), IEEE Harry Goode Memorial Award (2005), Computing Research Association’s Distinguished Service Award (2007), ACM Karl V. Karlstrom Outstanding Educator Award (2009), IEEE John von Neumann Medal (2010), and China’s Friendship Medal (2016), China’s highest recognition for a foreigner. In addition, the Chinese Academy of Sciences has designated him an Einstein professor.
He has honorary degrees from Seattle University, the National College of Ireland, the University of Sydney, St. Petersburg State University in Russia, Beijing University of Technology, and Hong Kong University of Science and Technology, and is an honorary professor of the Beijing Institute of Technology, Shanghai Jiao Tong University, Chongqing University, Yunnan University, and Peking University.
He received his BS (1961) from Seattle University and his MS (1962) and PhD (1964) in electrical engineering from Stanford University.
The AI Revolution
There is an information revolution taking place driven by artificial intelligence. The revolution started with the support vector machine model 15 or 20 years ago but has recently been driven by deep learning. Deep learning has had tremendous success in many application areas but little is known as to why it works so effectively.
This talk will review the basics of machine learning and then present some interesting research directions in deep learning.