- Doctor of Philosophy (Ph.D.), Computer Mathematics (Linz - Austria). March 2015
- Master's Degree, Soft Computing and Intelligent Data Analysis (Asturias - Spain). July 2011.
- Bachelor's Degree, Computer Science Engineer (Asturias - Spain). December 2002.
Articles in Peer-Reviewed Journals:
- F. Serdio, E. Lughofer, K. Pichler, M. Pichler, T. Buchegger and H. Efendic, Fuzzy Fault Isolation using Gradient Information and Quality Criteria from System Identification Models, Information Sciences, (revision submitted).
- F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic, Fault Detection in Multi-Sensor Networks based on Multivariate Time-Series Models and Orthogonal Transformations, Information Fusion, vol. 20, pp. 272-291, 2014.
- F. Serdio, E. Lughofer, K. Pichler, T. Buchegger and H. Efendic, Residual-Based Fault Detection using Soft Computing Techniques for Condition Monitoring at Rolling Mills, Information Sciences, vol. 259, pp. 304-320, 2014.
Articles in Peer-Reviewed Conferences (see talks in slide share):
- F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic, Reducing False Positives for Residual-Based On-line Fault Detection by Means of Filters, IEEE International Conference on Systems, Man and Cybernetics, SMC 2014, San Diego, USA, pp. 2803-2808.
- F. Serdio, A.-C. Zavoianu, E. Lughofer, K. Pichler, T. Buchegger and H. Efendic, Hybrid Genetic-Fuzzy Systems for Improved Performance in Residual-Based Fault Detection, World Congress on Natural and Biologically Inspired Computing, NaBIC 2014, Porto, Portugal, 2014, pp. 91-96.
- F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic, Gradient-based Fault Isolation for Residual-based Fault Detection Systems, IEEE World Congress on Computational Intelligence, WCCI 2014, Beijing, China, 2014, pp. 1428-1435.
- F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic, Multivariate Fault Detection using Vector Autoregressive Moving Average and Orthogonal Transformation in the residual Space, Annual Conference of the Prognostics and Health Management Society, PHM 2013, New Orleans, LA, USA, 2013, pp. 548-555.
F. Serdio, E. Lughofer, K. Pichler, T. Buchegger and H. Efendic, Data-Driven Residual-Based Fault Detection for Condition Monitoring in Rolling Mills, Proceedings of the IFAC Conference on Manufacturing Modeling, Management and Control, MIM '2013, St. Petersburg, Russia, 2013, pp. 1546-1551. (Winner of MIM 2013 Best paper award)
- By mistake the paper is indexed with its preliminary title "Condition Monitoring at Rolling Mills with Data-Driven Residual-Based Fault Detection"
Reviewer in Peer-Reviewed Journals:
- Expert Systems with Applications. Publisher: Elsevier.
- Soft Computing. Publisher: Springer.
- Expert Systems with Applications. Publisher: Aerospace & Electronic Systems Society.
Presentations at International Scientific Events:
- F. Serdio, Fault Detection and Isolation without Expert Knowledge, International Student Conference on Applied Mathematics and Informatics, ISCAMI 2014, Malenovice, Czech Republic, 2014.
More detailed information:
- Up-to-date curriculum, including commercial experience, in my profile in LinkedIn
- FoDok (Forschungsdokumentation), from Johannes Kepler University
Some other stuff maybe you like:
- Matlab framework for Genetic Algorithms. Free to use, just quote me :)
- Condition Monitoring with Data-Driven Models: Strategic Project with ACCM (Area 6)