Pierre Baldi is a chancellor’s professor of computer science at University of California Irvine and the director of its Institute for Genomics and Bioinformatics.
Pierre Baldi received his Bachelor of Science and Master of Science degrees at the University of Paris, in France. He then obtained his Ph.D. degree in mathematics at the California Institute of Technology in 1986 supervised by R. M. Wilson.
From 1986 to 1988, he was a postdoctoral fellow at the University of California, San Diego. From 1988 to 1995, he held faculty and member of the technical staff positions at the California Institute of Technology and at the Jet Propulsion Laboratory, where he was given the Lew Allen Award for Research Excellence in 1993. He was CEO of a start up company called Net-ID from 1995 to 1999 and joined University of California, Irvine in 1999.
Baldi’s research interests include artificial intelligence, statistical machine learning, and data mining, and their applications to problems in the life sciences in genomics, proteomics, systems biology, computational neuroscience, and, recently, deep learning.
Baldi has over 250 publications in his field of research and five books including
- “Deep Learning in Science”, Cambridge University Press, 2021.
- “Bioinformatics: the Machine Learning Approach” (MIT Press, 1998; 2nd Edition, 2001, ISBN 978-0262025065) a worldwide best-seller
- “Modeling the Internet and the Web. Probabilistic Methods and Algorithms“, by Pierre Baldi, Paolo Frasconi and Padhraic Smyth. Wiley editors, 2003.
- “The Shattered Self—The End of Natural Evolution“, by Pierre Baldi. MIT Press, 2001.
- “DNA Microarrays and Gene Regulation“, Pierre Baldi and G. Wesley Hatfield. Cambridge University Press, 2002.
Baldi is a fellow of the Association for the Advancement of Artificial Intelligence (AAAI), the AAAS, the IEEE,and the Association for Computing Machinery (ACM). He is also the recipient of the 2010 Eduardo R. Caianiello Prize for Scientific Contributions to the field of Neural Networks and a fellow of the International Society for Computational Biology (ISCB).
Deep learning algorithm solves Rubik’s Cube faster than any human.
https://news.uci.edu/2019/07/15/uci-researchers-deep-learning-algorithm-solves-rubiks-cube-faster-than-any-human/
AI solves Rubik’s Cube in one second
https://www.bbc.com/news/technology-49003996
