Madeleine
Seeland,
Dipl.-Wirt.-Inf.
Ph.D. student
Room: 01.09.040Institut für Informatik / I12
Boltzmannstr. 3
85748 Garching b. München, Germany
Research Interests:
machine learning, data mining, toxicology, bioinformatics, cheminformatics, algorithms for small molecules, graph algorithms
Publications:
Selected Talks and Tutorials:
Talks:
- Seeland, M, Kramer,S and Pfahringer, B (2012) Maximum Common Subgraph Based Locally Weighted Regression 2012, Riva del Garda, Italy
- Seeland, M, Berger, S A, Stamatakis, A and Kramer,S (2011) Parallel Structural Graph Clustering at the ECML/PKDD 2011, Athen, Greece
- Seeland, M, Girschick, T, Buchwald, F and Kramer,S
(2010) Online Structural Graph Clustering using Frequent Subgraph Mining at the ECML/PKDD 2010, Barcelona, Spain
Posters:
- Seeland, M, Berger, S A, Stamatakis, A and Kramer,S (2011) Parallel Structural Graph Clustering at the ECML/PKDD 2011, Athen, Greece
- Seeland, M, Berger, S A, Girschick, T, Stamatakis, A and Kramer,S (2011). Parallel Structural Graph Clustering At: OpenTox InterAction Meeting 2011, Munich, Germany
- Seeland, M, Girschick, T, Buchwald, F and Kramer,S
(2010) Online Structural Graph Clustering using Frequent Subgraph Mining at the ECML/PKDD 2010, Barcelona, Spain
- Seeland, M, Girschick, T, Buchwald, F and Kramer,S (2010), Clustering Structure Databases Using Frequent Substructure Mining, 18th European Symposium on Quantitative Structure-Activity Relationships, Rhodes, Greece
Short Scientific CV:
I studied Management Information Systems at the University of Mannheim and spent one year abroad at the University of Waterloo in Canada. I wrote my diploma thesis at the Brigham and Women's Hospital and Harvard Medical School in Boston. The topic of my thesis was "Development and Validation of a Two-Tensor Tractography Navigation System for Neurosurgery".
I am currently working on my PhD in the Machine Learning and Data Mining in Bioinformatics group, in collaboration with the Fraunhofer Institut für Toxikologie und experimentelle Medizin (ITEM), the University of Freiburg and the Charité Universitätsmedizin Berlin. The goal of the project is to develop strategies for building and defining new categories for the endpoints of sub-acute, sub-chronic and chronic toxicity.
Teaching:
Supervised Theses
- Jonathan Boidol; "Local Models for the Prediction of Differences in Biological Activity", 2011. (Bachelor Thesis)
(Co-)Reviewing
- European Conference on Machine Learning/European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-2010, 2011)
- IEEE International Conference on Data Mining (ICDM-2010)
- ACM Symposium on Applied Computing (ACM SAC-2011, 2013)
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2011)
- International Conference of Machine Learning (ICML- 2011)
- International Conference on Discovery Science (DS-2011)
- International Conference on Extending Database Technology (EDBT-2012)
- Asian Conference on Machine Learning (ACML 2012)
