Professor Dr. Stefan Faußer
Professor für Data Analytics
Studiengangleiter Master of Artificial Intelligence and Data Analytics
Studiengangleiter Digital Enterprise Management
Studiengangleiter Künstliche Intelligenz und Informationsmanagement
Senior Research Fellow am Institut für Digitale Innovation (IDI)
Lehrveranstaltungen
- Big Data and Artificial Intelligence
- Deep Learning
- Machine Learning
- Big Data
- Business Intelligence (Methods and Tools for Data Analysis and Reporting)
- Car Entertainment and Advanced Driver Assistance Systems
- Angewandte Statistik und Mathematik (Mathematik und Statistik)
Vorherige Lehrveranstaltungen/ previous lectures:
- Natural Language Processing (AIDA Master)
- Predictive Analytics and Data Mining (BIA Master)
- BI Platforms and Tools (BIA Master)
- Datenbanken (IMUK Bachelor)
Vita
- Seit September 2020 Professor für Data Analytics an der Hochschule für angewandte Wissenschaften Neu-Ulm (HNU)
- Promotion in theoretischer Informatik an der Universität Ulm, Institut für Neuroinformatik. Schwerpunkte: Reinforcement Learning Ensembles und Methoden zur Bildung nicht-sphärischer Cluster aus großen Datenmengen
- Studium der Informatik an der Universität Ulm (Master) und an der Hochschule Ravensburg-Weingarten (FH-Diplom)
- Von 2018 - 2020 Data Scientist und IT-Projektleiter für die digitalen Services der professionellen Kaffeemaschinen (IoT Devices) bei WMF Group GmbH in Geislingen
- Von 2016 - 2017 Data Scientist für die TeamViewer Software Produkte bei TeamViewer GmbH in Göppingen
- Von 2008 - 2016 Software Engineer im Embedded Bereich bei der Real-Time Systems GmbH in Ravensburg
Publikationen
- Jechle, Deinera and Faußer, Stefan and Gewald, Heiko (2026) Lies or Nerves? A Signal Detection Theory-Guided Approach to Deception Detection in Natural Speech. (öffnet neues Fenster) In: (Proceedings of the) 9th International Conference on Information Technology & Systems (ICITS), February, 16-18, 2026, Roatán Island, Honduras, pp. 224-236, Paper 312 / Full Paper. (Lecture Notes in Networks and Systems; 1967). ISBN 9783032275417
- Finze, Nikola and Jechle, Deinera and Faußer, Stefan A. and Gewald, Heiko
(2024)
How are We Doing Today? Using Natural Speech Analysis
to Assess Older Adults’ Subjective Well-Being. (öffnet neues Fenster)
Business & Information Systems Engineering : BISE, 66.
pp. 321-334.
ISSN 1867-0202
Volltext abrufen - Vangeepuram, Madhurima and Ehm, Hans and Ratusny, Marco and Faußer, Stefan A. and Heilmayer, Stefan and Welling, Tobias L.
(2023)
Assessing delivery commitments in supply chains : A matrix-based framework. (öffnet neues Fenster)
In: (Proceedings of the) Winter Simulation Conference (WSC) "Simulation for Resilient Systems", December, 10-13, 2023, San Antonio, TX, USA, pp. 2182-2193.
ISBN 9798350369663
Volltext abrufen - Meyer, Dany and Faußer, Stefan A. (2023) A framework for the design, implementation and evaluation of ai based real-life learning scenarios for computer science non-majors. (öffnet neues Fenster) In: (Proceedings of the) International Conference on Education, Research and Innovation (ICERI), November, 13-15, 2023, Seville, Spain. ISBN 9788409559428
- Gebele, Jens and Brune, Philipp and Faußer, Stefan A. (2022) Face Value: On the Impact of Annotation (In-)Consistencies and Label Ambiguity in Facial Data on Emotion Recognition. (öffnet neues Fenster) In: (Proceedings of the) 26th International Conference on Pattern Recognition (ICPR), August, 21-25, 2022, Montreal, QC, Canada, pp. 2597-2604. ISBN 9781665490627
- Thaler, Fabian and Faußer, Stefan A. and Gewald, Heiko
(2021)
Using NLP to analyze whether customer statements comply with their inner belief. (öffnet neues Fenster)
arXiv:2107.11175.
Volltext abrufen - Messer, Uwe and Faußer, Stefan
(2020)
Machine Learning Infusion in Service Processes. (öffnet neues Fenster)
In:
Automatisierung und Personalisierung von Dienstleistungen: Methoden–Potenziale–Einsatzfelder / Bruhn, Manfred; Hadwich, Karsten (Hrsg.).
Wiesbaden: Springer, pp. 343-364.
(Forum Dienstleistungsmanagement).
ISBN 9783658301682
Volltext abrufen - Faußer, Stefan A. and Schwenker, Friedhelm (2015) Selective neural network ensembles in reinforcement learning: Taking the advantage of many agents. (öffnet neues Fenster) Neurocomputing, 169. pp. 350-357. ISSN 0925-2312
- Faußer, Stefan A.
(2015)
Large state spaces and large data: Utilizing neural network ensembles in reinforcement learning and kernel methods for clustering. (öffnet neues Fenster)
Dissertation thesis, Universität Ulm.
Volltext abrufen - Faußer, Stefan A. and Schwenker, Friedhelm
(2015)
Neural Network Ensembles in Reinforcement Learning. (öffnet neues Fenster)
Neural Processing Letters, 41.
pp. 55-69.
ISSN 1573-773X
Volltext abrufen - Faußer, Stefan A. and Schwenker, Friedhelm
(2014)
Selective Neural Network Ensembles in Reinforcement Learning. (öffnet neues Fenster)
In: (Proceedings of the) 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), 23.-25. April 2014, Bruges, Belgium, pp. 105-110.
ISBN 9782874190957
Volltext abrufen - Faußer, Stefan A. and Schwenker, Friedhelm (2014) Semi-supervised Clustering of Large Data Sets with Kernel Methods. (öffnet neues Fenster) Pattern Recognition Letters, 37. pp. 78-84. ISSN 0167-8655
- Faußer, Stefan A. and Schwenker, Friedhelm (2012) Clustering large datasets with kernel methods. (öffnet neues Fenster) In: (Proceedings of the) 21st International Conference on Pattern Recognition. (ICPR ’12) ; Vol. 1, November, 11-15th, 2012, Tsukuba, Japan, pp. 501-504. ISBN 9781467322164
- Faußer, Stefan A. and Schwenker, Friedhelm (2012) Semi-Supervised Kernel Clustering with Sample-to-cluster Weights. (öffnet neues Fenster) In: (Proceedings of the) 1st IAPR TC3 Workshop, PSL 2011, 15.-16. September 2011, Ulm, Germany, pp. 72-81. ISBN 9783642282577
- Faußer, Stefan A. and Schwenker, Friedhelm (2011) Ensemble Methods for Reinforcement Learning with Function Approximation. (öffnet neues Fenster) In: (Proceedings of the) 10th International Workshop on Multiple Classifier Systems (MCS), June, 15-17, 2011, Naples, Italy, pp. 56-65. ISBN 9783642215568
- Faußer, Stefan A. and Schwenker, Friedhelm (2010) Learning a Strategy with Neural Approximated Temporal-Difference Methods in English Draughts. (öffnet neues Fenster) In: (Proceedings of the) 20th International Conference on Pattern Recognition (ICPR), August, 23-26, 2010, Istanbul, Turkey, pp. 2925-2928. ISBN 9781424475421
- Faußer, Stefan A. and Schwenker, Friedhelm (2010) Parallelized Kernel Patch Clustering. (öffnet neues Fenster) In: (Proceedings of the) 4th IAPR TC3 Conference on Artificial Neural Networks in Pattern Recognition (ANNPR), April, 11-13, 2010, Cairo, Egypt, pp. 131-140. ISBN 9783642121586
- Faußer, Stefan A. and Schwenker, Friedhelm (2008) Neural Approximation of Monte CarloPolicy Evaluation Deployed in Connect Four. (öffnet neues Fenster) In: (Proceedings of the) 3rd IAPR Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), July, 2-4, 2008, Paris, France, pp. 90-100. ISBN 9783540699385
Forschung
Forschungsprojekte
- Voice Analysis for Customer Emotions (VACE)
