Dr. Patrick Traxler

Researcher Data Analysis Systems
Telefon: +43 7236 3343 896
Fax: +43 7236 3343 888

Data Science - DAS

Dr. Patrick Traxler leads the research team for Data Analysis Algorithms at the SCCH. He studied computer science at TU Vienna and has received his doctoral degree from ETH Zurich in July 2010. From 2006 to 2009, he worked as a scientific assistant at the Institute of Theoretical Computer Science at ETH Zurich. His responsibilities comprised research in the area of algorithms and complexity and teaching assistance for algorithms and programming courses. From January 2011 to October 2012, he worked at the Institute of Ubiquitous Meteorology (UBIMET), an international meteorological company. He has been working at SCCH since November 2012.

The focus of his research lies in the areas of algorithms, diagnosis, and optimization. The goals of his research are the integration and application of these three disciplines. He approaches fault diagnosis and detection problems via machine learning and combines learning-based and knowledge-based methods. Combining learning-based and knowledge-based methods is a central concern of artificial intelligence. In addition, he works on learning algorithms with guaranteed robustness by designing and analyzing optimization algorithms. During his career, Dr. Traxler gathered experience with applying these approaches to application areas such as renewable energy and meteorology, analysis of technical systems and (discrete) manufacturing processes.

Selected publications

  • A. Kogler, P. Traxler. Parallel Empirical Risk Minimization, submitted, 2017.
  • A. Kogler, P. Traxler. Efficient and Robust Median-of-Medians Algorithms with Applications to Fault Detection, 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC2016), 2016.
  • P. Traxler, T. Grill, P. Gomez. A Robust Alternative to Correlation Networks for Identifying Faulty Systems, 26th International Workshop on Principles of Diagnosis, 2015.
  • P. Traxler. The Relative Exponential Time Complexity of Approximate Counting Satisfying Assignments, to appear in Algorithmica (Special Issue), 2016. An extended abstract appeared in 9th International Symposium on Parameterized and Exact Computation, 2014.
  • P. Traxler. Variable Influences in Conjunctive Normal Forms, 12th International Conference Theory and Applications of Satisfiability Testing, pages 101-113, 2009.

Selected research projects

  • Since 2015, Jan.: COMET-project inFADIA
  • Since 2014, Sept.: EStore-M (EraSME; FFG Nr. 836684)
  • Since 2013, Sept.: Smart Maintenance (FFG Nr. 843650)
  • 2012, Jan. - 2014, Dec.: COMET-project modDiscovery