Jesse Davis

Jesse Davis is a Professor at the Department of Computer Science, KU Leuven, actively contributing to the Machine Learning group and the Sports Analytics Lab. He is part of the Faculty of Engineering Science and the Leuven.AI Institute.

• Ph.D. in Computer Sciences from University of Wisconsin-Madison (2007)
• M.S. in Computer Sciences from University of Wisconsin-Madison (2005)
• B.A. in Computer Science from Williams College (2002)

His research focuses on machine learning, data mining, big data analytics, and sports analytics, with significant work in:

• Transfer learning and Markov logic networks
• Anomaly detection and semi-supervised learning
• Medical NLP and biomechanical data analysis
• Soccer performance metrics and tactical analysis

His recent work explores spatio-temporal data analysis in sports and explainable AI for medical applications, with collaborations spanning finance, healthcare, and semiconductor manufacturing.

Notable scientific awards include:

• Best Paper Award (Applied Data Science Track) at KDD 2019
• Best Technical Paper Award at Intelligence Analysis Workshop

He advises numerous PhD and Master's students in areas like:

• Football analytics
• Tree ensemble compression
• Medical question-answering systems
• Biomechanical load prediction

His lab develops tools such as:

• GSSL for Markov network structure learning
• TODTLER for transfer learning
• Alchemy system for Markov logic networks