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JÜRGEN SCHMIDHUBER

Professor, Computer Science | Co-Chair, Center of Excellence for Generative AI

Computer, Electrical and Mathematical Science and Engineering Division 
Center membership :
KAUST Artificial Intelligence Initiative

juergen.schmidhuber@kaust.edu.sa


Affiliations

Education Profile

  • Habilitation August 1993: qualification for tenure professorship in computer science, Technische Universität München (TUM).
  • Ph.D. 1988-1991: preparation of a Ph.D. thesis on "Dynamic Neural Nets and the Fundamental Spatio-Temporal Credit Assignment Problem" at TUM.
  • Diploma 1983 - 1987: 4 year study of computer science and mathematics at Technische Universität München (TUM).

Research Interests

Jürgen Schmidhuber is Co-Chair of the King Abdullah University of Science and Technology (KAUST) Center for Generative Artificial Intelligence (GenAI), and professor of the Computer Science program in the Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) division. Prior to joining KAUST, he worked as Scientific Director of the Swiss AI Lab, IDSIA, and as professor of Artificial Intelligence (Ordinarius) at the University of Lugano (USI) from 2009-2021. He is most noted for his pioneering work in the field of artificial intelligence (AI), deep learning, and artificial neural networks. In 1990-91, he laid foundations of GenAI by introducing the principles of Generative Adversarial Networks (now used for deepfakes), unnormalised linear Transformers (see the T in ChatGPT), and self-supervised Pre-Training for deep learning (see the P in ChatGPT). His lab also produced LSTM, the most cited AI of the 20th century, and the Highway Net (a variant of which is the most cited AI of the 21st century). Elon Musk tweeted: "Schmidhuber invented everything." His AI is on over 3 billion smartphones, and used many billions of times per day. Supported by excellent hardware and KAUST's outstanding interdisciplinary expertise in many different areas of science (see the KAUST Discovery Magazines), the GenAI Center will focus on AI applications in all fields, including healthcare, drug design, chemistry, materials science, speech recognition and natural language processing, automation, robotics, soft robotics, and other areas. The KAUST GenAI also boasts an outstanding visual computing team, which has regularly been among the top groups at leading conferences in computer vision (e.g., the Conference on Computer Vision and Pattern Recognition), computer graphics, etc.

Selected Publications

  • Prof. Schmidhuber's list of Publications on Dblp
  • Prof. Schmidhuber's list of Citations on Google Scholar
  • Prof. Schmidhuber's list of Publications on IEEE Xplore Digital Library