DI Johannes Himmelbauer

Researcher Data Analysis Systems
Phone: +43 50 343 830


Data Science - DAS

M. Mayr, J. Himmelbauer. Detecting anomalies in production quality data using a method based on The Chi-Square Test Statistic. In M. Song, I. Song, G. Kotsis, A. Tjoa, I. Khalil (editors), DaWaK 2020: Big Data Analytics and Knowledge Discovery, Lecture Notes in Computer Science, volume 12393, pages 348-363, DOI 10.1007/978-3-030-59065-9_27, Springer, September, 2020.

L. Ehrlinger, C. Lettner, J. Himmelbauer. Tackling semantic shift in industrial streaming data over time. In M. Crowe, L. Ehrlinger, F. Laux, A. Schmidt (editors), Proceedings of the 12th International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2020), pages 36-39, IARIA, October, 2020.

J. Himmelbauer, J. Martínez Gil, M. Ksen, K. Linner, S. Plakolm. Towards a data-driven approach for fraud detection in the social insurance field: A case study in Upper Austria. In A. Kö, E. Francesconi, G. Anderst-Kotsis, A. Tjoa, I. Khalil (editors), Electronic Government and the Information Systems Perspective - Proc. EGOVIS 2019, Lecture Notes in Computer Science, volume 11709, pages 70-84, DOI 10.1007/978-3-030-27523-5_6,, Springer, August, 2019.

R. Ramler, J. Himmelbauer, T. Natschläger. Building defect prediction models in practice. In I. Ghani, W. Wan Kadir, M. Ahmad (editors), Handbook of Research on Emerging Advancements and Technologies in Software Engineering, pages 540-565, IGI Global, April, 2014.

R. Ramler, J. Himmelbauer. Noise in bug report data and the impact on defect prediction results. Proceedings of the Joint Conference of the 23rd International Workshop on Software Measurement (IWSM) and the Eighth International Conference on Software Process and Product Measurement (Mensura), pages 173-180, October, 2013.

M. Zhariy, J. Himmelbauer, M. Scheerer. Sparse signal processing technique in multimodal dispersive SHM. In F. Chang (editor), Proceedings of the 9th International Workshop on Structural Health Monitoring (IWSHM 2013), pages on CD paper No. 1243, September, 2013.

J. Bouchot, J. Himmelbauer, B. Moser. On autocorrelation based on Hermann Weyl's discrepancy norm for time series analysis. In A. Prieto (editor), Proceedings of the IEEE World Congress on Computational Intelligence (WCCI 2010), pages 3139 - 3145, IEEE, July, 2010.

E. Klement, E. Lughofer, J. Himmelbauer, B. Moser. Data-driven and knowledge-based modeling. In B. Buchberger, M. Affenzeller, A. Ferscha, M. Haller, T. Jebelean, E. Klement, P. Paule, G. Pomberger, W. Schreiner, R. Stubenrauch, R. Wagner, G. Weiß, W. Windsteiger (editors), pages 237-280, Springer, June, 2009.

T. Natschläger, J. Himmelbauer, H. Schöner, F. Kokert, S. Mitter, H. Exner. Wissensextraktion mittels maschinellen Lernens zum besseren Prozessverständnis in der Stahlerzeugung. Tagungsband Industrielles Symposium Mechatronik Automatisierung, pages 79-87, Clusterland Oberösterreich GmbH / Mechatronik-Cluster, October, 2008.

M. Drobics, J. Himmelbauer. Creating comprehensible regression models. Soft Computing - A Fusion of Foundations, Methodologies and Applications, volume 11, number 5, pages 421-438, March, 2007.

J. Himmelbauer, M. Drobics. Regularized numerical optimization of fuzzy rule bases. Proc. 13th IEEE Int. Conf. on Fuzzy Systems, pages 1655 - 1660, IEEE Press, July, 2004.