Scholar
Jesse Davis
Google Scholar ID: gz74XOYAAAAJ
Professor, Department of Computer Science, KU Leuven
Citations & Impact
Citations
10,230
H-index
36
i10-index
98
Publications
20
Co-authors
14
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Research on soccer analytics was profiled by The Guardian; member of the AI working group for the International Olympic Committee that produced their AI Agenda; involved with an initiative to develop a Common Data Format (CDF) for data arising from football (soccer) matches; paper 'Leaving Goals on the Pitch' presented at the MIT Sloan Sports Analytics Conference, covered by fivethirtyeight; co-founder of spinoff Runeasi, launched in December 2020; paper on 'valuing on-the-ball actions' in soccer received the Best Paper Award in the ADS track at KDD 2019, discussed in The Economist and ESPN.
Research Experience
- Post-doctoral research with Pedro Domingos at the University of Washington, working on Markov logic networks which are publicly available as the Alchemy system; involved with the MURI project entitled 'A Unified Approach to Abductive Inference'.
Education
- Ph.D. in Computer Sciences from the University of Wisconsin-Madison (August 2007), supervised by David Page; M.S. in Computer Sciences from the University of Wisconsin-Madison (May 2005); B.A. in Computer Science from Williams College (June 2002).
Background
- Research interests span machine learning, data mining, big data, artificial intelligence, and sports analytics. Currently a professor at the Department of Computer Science, KU Leuven, and a member of the Machine Learning group within the Declarative Languages and Artificial Intelligence Lab (DTAI).
Miscellany
- Maintains a number of sports-related software packages, many of which have open source implementations.
