Thomas Gaertner (Alumni)

University of Bonn and Fraunhofer IAIS
Computational Aspects of Mining and Learning
Tel.: +49 2241 14 3513    E-Mail: thomas.gaertner iai.uni-bonn.de
I am more actively maintaining http://www.thomasgaertner.org
Schloss Birlinghoven
53757 Sankt Augustin

"Our critics are our friends, because they show us our faults." - Benjamin Franklin
"Even if you're on the right track, you'll get run over if you just sit there" - Will Rogers


Overview | Publications | Activities | Research Interests | CV ]


Some selected publications are listed below and can see the complete list by clicking `show all' above. I am trying to keep the list up to date but it is more likely that my [@scholar/citations] profile is more up to date. You can also look [@DBLP], [@springer], [@scholar], or [@acm]. Now there is also a list [@microsoft academic search].

Overview | Publications | Activities | Research Interests | CV ]


  • Action Editor since 2009 and Editorial Board Member since 2006 of the Machine Learning Journal ( MLJ )
  • PhD Committees Koen Smets (University of Antwerp), Martial Hue (Ecole des Mines de Paris), Wannes Meert (KU Leuven), Licentiate discussion leaer Frederik Johansson (Chalmer University of Technology)
  • Funding
    • I received an Emmy Noether grant in 2010 for Machine Learning Algorithms for Constructing Novel Relational Structures
    • My project on Effective Well-Behaved Pattern Mining through Sampling is funded by a research grant from the DFG
  • Organisation
    • member of the technical organisation committee of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, which will be held in Riva del Garda in 2016.
    • co-chair of the first worksop on Constructive Machine Learning at NIPS 2013
    • co-chair of the first worksop on Mining and Learning with Graphs at ECMLPKDD 2016
    • co-chair of the project workshop on Learning and Inference
  • Tutorials, Colloquia, Invited Talks, ...
    • In 2014 I gave invited talks at the ECML workshop on New Frontiers in Mining Complex Patterns, at Microsoft Research in Remond, at the Tokyo Institute of Technology, and at Chalmers University of Technology. Thanks to my hosts!
    • Algorithms for Predicting Structured Data tutorial with Shankar Vembu at the European Conference on Machine Learning ( more details )
    • Kernels for Structured Data tutorial at the International Conference on Machine Learning  ( more details ).
    • Kernel-Based Learning from Structured Data at the 2002 Summer School on Relational Data Mining in Helsinki. [handouts]
  • Recent Programm Committee Memberships
    • International Conference on Machine Learning ( regularly PC member or Area Chair )
    • Conference on Artificial Intelligence ( Senior PC member AAAI-2010 )
    • International Joint Conference on Artificial Intelligence ( IJCAI-2009 | Senior PC member IJCAI-2011 )
    • European Conference on Machine Learning ( regularly Area Chair or PC member, regularly journal track guest editorial board member )
    • International Word Wide Web Conference ( WWW-2010 )
    • International Conference on Knowledge Discovery and Data Mining ( regularly PC member )
    • International Workshop on Mining and Learning with Graphs ( regularly PC member | Workshop Co-Chair MLG-2006 | Steering Committee MLG-2007 | Steering Committee MLG-2008 )
  • Guest Editor Machine Learning special issue on Mining and Learning with Graphs
  • Research Proposal Evaluation
    • German Science Foundation ( DFG )
    • The Israel Science Foundation ( ISF ),
    • Research Foundation Flanders ( FWO )
Overview | Publications | Activities | Research Interests | CV ]

Research Interests

My main research interests are efficient and effective machine learning and data mining algorithms. Machine learning considers the problem of extracting useful functional or probabilistic dependencies from a sample of data. Such dependencies can then, for instance, be used to predict properties of partially observed data. Data mining is often used in a broader sense and includes several different computational problems, for instance, finding regularites or patterns in data. By efficiency I mean on the one hand the classical computational complexity of decision, enumeration, etc problems but on the other hand also a satisfactory response time that allows for effectiveness. By effectiveness I mean how well an algorithm helps to solve a real world problem.


Overview | Publications | Activities | Research Interests | CV ]

CV (Curriculum Vitae)

I earned a PhD from the University of Bonn (summa cum laude), a MSc from the University of Bristol (with commendation), and a Diplom as well as a degree as a certified engineering assistant from the University of Cooperative Education in Mannheim. During the course of my studies at the University of Bristol, I got interested in machine learning research. Since then, I have created a track record of publications at the highest ranking machine learning and data mining conferences. I investigate theoretical and algorithmical challenges of machine learning and data mining. I am always interested in applications of these algorithms and have for instance worked on chemoinformatics, computer games, sports analytics, and financial time series. Internationally, I am best known for my work on kernels for structured data. In 2010, I received an Emmy Noether grant from the German Science Foundation. I regularly supervise students of all levels, organise seminars and labs, teach courses on kernel methods, and am give tutorials as well as invited talks. I am an action editor of the `Machine Learning' journal and member of the technical organisation committee of the `European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases', which will be held in Riva del Garda in 2016.


Overview | Publications | Activities | Research Interests | CV ]

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