Leander Schietgat
homepage:http://people.cs.kuleuven.be/~leander.schietgat/Welcome.html
search externally:   Google Scholar,   Springer,   CiteSeer,   Microsoft Academic Search,   Scirus ,   DBlife

Description

I am a PhD student working in Machine Learning, a subgroup of the Declarative Languages and Artificial Intelligence group, situated in the Department of Computer Science of the Katholieke Universiteit Leuven. My supervisors are Hendrik Blockeel and Maurice Bruynooghe.

My research interests include biological applications of machine learning and (relational) data mining. I am particularly interested in techniques that use graphs, either as input or output. One area where I am working in is functional genomics, where the task is to predict the functions of genes. Since these functions are organized in a hierarchy, the output of the learning method is a directed acyclic graph. Another application I am working on is the classification of molecules. By representing molecules as graphs, it is possible to exploit certain properties, which can be used to develop efficient algorithms.

I am supported by the Institute for the Promotion of Innovation through Science and Technology in Flanders.


Lectures:

lecture
flag A Polynomial-time Metric for Outerplanar Graphs (Extended Abstract)
as author at  Talks,
2984 views
  lecture
flag Hierarchical Multilabel Classification Trees for Gene Function Prediction
as author at  Workshop on Probabilistic Modeling and Machine Learning in Structural and Systems Biology (PMSB), Tuusula 2006,
4555 views