
About
Thomas Gärtner is a Full Professor of Machine Learning at TU Wien (Technical University of Vienna), leading the Machine Learning Research Unit (E 194-06). He previously held professorships at the University of Nottingham and the University of Bonn. His research focuses on efficient and effective machine learning algorithms, particularly in structured data domains like graphs and chemical compounds. Key areas include kernel methods, active learning, and graph neural networks. He is involved in projects such as NanoX (Austrian Science Fund) and StruDL (Vienna Science Fund), addressing challenges in structured data learning and trustworthy AI.
Education: PhD from University of Bonn (2005), MSc from University of Bristol (2000), Diplom from University of Cooperative Education (1999).
Research Interests: Machine Learning, Data Mining, Kernel Methods, Chemoinformatics, Graph Neural Networks, Active Learning, and Constructive Machine Learning. His work emphasizes real-world applications in chemistry and computer games.
Grants & Awards: Emmy Noether Grant (2010), Best Paper Award (2016), ICLR Area Chair (2021), and recognition for contributions to EPSRC peer review (2020).
Teaching: Offers courses like 'Introduction to Machine Learning' and 'Theoretical Foundations of Machine Learning.' Supervises PhD and diploma students in advanced topics such as graph algorithms and neural network distillation.
Lab/Teams: Heads the Machine Learning Research Unit and collaborates with the competence center ML2R (Rhine-Ruhr region). Active in organizing ECML PKDD conferences and workshops on constructive machine learning.
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