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Andreas Hapfelmeier, Dipl.-Bioinf.

Andreas Hapfelmeier, Dipl.-Bioinf.

Research Interests:

Machine learning and data mining on medical data, predictive modeling, online learning


Awards:

Best application paper award at ICDM 2008


Activities:

  • (Co-)Reviewing:

 

  • IEEE International Conference on Data Mining (ICDM): 2008, 2009, 2010
  • ACM Symposium on Applied Computing (SAC): 2009, 2010, 2011
  • International Conference on Data Warehousing and Knowledge Discovery (DaWak): 2009
  • International Conference on Discovery Science (DS): 2009
  • European Conference on Machine Learning/European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD): 2009, 2010, 2011
  • International Conference on Inductive Logic Programming (ILP): 2009
  • LeGo: 2008
  • SIAM International Conference on Data Mining (SDM): 2009, 2010
  • International Conference on Machine Learning (ICML): 2010

Publications:

Hapfelmeier, A, Schmidt, J, and Kramer, S (2013).
Incremental Linear Model Trees on Massive Datasets: Keep it Simple, Keep it Fast
In: Proceedings of the 28th Symposium On Applied Computing, accepted.

Schmidt, J, Hapfelmeier, A, Ghorbani, A, and Kramer, S (2013).
Learning Probabilistic Real-Time Automata from Multi-Attribute Event Logs
Intelligent Data Analysis Special Issue on Dynak Topics, 7(1):to appear.

Hapfelmeier, A, Mertes, C, Schmidt, J, and Kramer, S (2012).
Towards Real-Time Machine Learning
In: ECML-PKDD 2012 Workshop: Instant Interactive Data Mining.

Schmidt, J, Hapfelmeier, A, Schmidt, W, and Wollina, U (2012).
Improving Wound Score Classification with Limited Remission Spectra
International Wound Journal, Wiley-Blackwell, 9(2):189-98.

Li, R, Hapfelmeier, A, Schmidt, J, Perneczky, R, Drzezga, A, Kurz, A, and Kramer, S (2011).
A case study of stacked multi-view learning in dementia research
In: Proceedings of the 13th Conference on Artificial Intelligence in Medicine, pp. 60–69, Bled, Slovenia, Springer-Verlag. Lecture Notes in Computer Science (LNCS).

Schmidt, J, Hapfelmeier, A, Müller, M, Pernetzky, R, Drzezga, A, Kurz, A, and Kramer, S (2010).
Interpreting PET Scans by Structured Patient Data: A Data Mining Case Study in Dementia Research
Journal of Knowledge and Information Systems (KAIS), 24:149-170.

Hapfelmeier, A, Schmidt, J, Müller, M, Pernetzky, R, Drzezga, A, Kurz, A, and Kramer, S (2008).
Interpreting PET Scans by Structured Patient Data: A Data Mining Case Study in Dementia Research
In: Proceedings of the Eighth IEEE International Conference on Data Mining (ICDM-2008), pp. 213-222.

Kramer, S, Aufschild, V, Hapfelmeier, A, Jarasch, A, Kessler, K, Reckow, S, Wicker, J, and Richter, L (2006).
Inductive Databases in the Relational Model: The Data as the Bridge
In: Proceedings of the Fourth International Workshop on Knowledge Discovery in Databases, pp. 124-138.


Short Scientific CV:

In my diploma project "subgroup discovery in Alzheimer data" at the TU München, I got in touch with data mining / machine learning in the area of medical data / health care. To intensify my research in this area I developed prediction models for the DxCG Gesundheitsanalytik GmbH. The task was to improve existing and find new algorithms to extract useful information from medical data. Currently, I am doing my PhD in the Machine Learning and Data Mining in Bioinformatics group, developing prediction models on huge data sets.

I am member of the CeDoSIA program.


Teaching:

  • Tutor Maschinelles Lernen und Data Mining in der Bioinformatik (WS 10/11)
  • Tutor Analyse strukturierter Daten in der Bioinformatik (SS 2010, SS 2011)
  • Tutor Hauptseminar Bioinformatik (WS 09/10, WS 10/11)
  • Tutor Proseminar Bioinformatik (SS 2009, SS 2011)
  • Tutor Informatik I für Ingenieure (WS 11/12)

 

  • Noelia Ruiz; "Ordering PET Scans: criterion and visualization", 2012 (Diploma Thesis, work in progress)
  • Christian Mertes; "Incremental linear model trees on changing data stream rates", 2011 (Bachelor Thesis)
  • Yassine Azyrit; "Implementation and comparison of incremental linear model trees in the MOA framework", 2011. (Diploma Thesis)
  • G. Zhang; "Improving the Usability of the Alzheimer`s Database AldBase", 2009. (Bachelor Thesis)