Dr. Sascha Meudt

Nach meinem Abitur 2001 an der Robert-Bosch-Schule Ulm als bester Absolvent im LF Technik habe ich zunächst bis 2003 Elektrotechnik mit anschließendem Wechsel in das Fach Informatik studiert. Das Informatik Studium habe ich 2011 mit der Diplomarbeit „Audio-visuelle Informationsfusion zur Identifikation von Personen bei der Mensch-Computer-Interaktion“ abgeschlossen. Studienbegleitend war ich selbständig im Bereich EDV Kursleitung, EDV Referent und Dienstleistung so wie Veranstaltungstechnik tätig. Seit Sommer 2011 bin ich am Institut für Neuroinformatik als wissenschaftlicher Mitarbeiter angestellt. Hier beschäftige ich mich mit der multimodalen Emotions- und Dispositionserkennung in der Mensch-Computer-Interaktion. 2019 habe ich meine Promotion mit der Dissertationschrift "Maschinelle Emotionserkennung in der Mensch-Maschine-Interaktion" abgechlossen.

Meinen privaten Blog, auf dem ich regelmäßig über meine Eigenbauprojekte (DIY) aus dem Tech-Bereich berichte finden Sie unter http://meudt.tech

• Künstliche Intelligenz 
• Maschinelles Lernen
• Mustererkennung
• Tiefe Neuronale Netze
• Partiell überwachtes Lernen
• (Teil-) Automatisierte Annotation / Aktives Lernen

• Mitglied im Sonderforschungsbereich
  Transregio 62 „Eine Companion-Technologie für kognitive technische Systeme“
  
• Doktorandensprecher des integrierten Graduiertenkollegs des SFB-TRR62

• Heiko Oppel Active learning in affective computing utilizing deep neuronal networks, Master Arbeit, 07/2019
• Venkatesh Srinivasan Deep Learning Algorithms for Emotion Recognition on Low Power Single Board Computers, Master Arbeit, 12/2018
• Patrick Kaiser Machine Learning Classifiers in the Analysis of Button Press Dynamics and fMRI Data in an Auditive Learning Experiment, Master Arbeit, 03/2018
• Stefan Gödecke Visualization and (explorative) Analysis of non-invasive Measurements in an Auditory Learning Experiment, Master Arbeit, 01/2018
• Julien Vincenot-Gassmann Maschinelle Lernverfahren zur Erkennung kognitiver Belastungen anhand mimischer Expression, Master Arbeit, 09/2017
• Sabine Wieluch Multimodal Active Learning in Affective Computing, Master Arbeit, 01/2017
• Dennis Held Bimodale Erkennung affektiver Zustände durch Ensemble Methoden anhand von Audio- und Biosignalens, Master Arbeit, 07/2016
• Florian Paust Recognition of Cognitive Load in Speech, Bachelor Arbeit, 07/2016
• Daniel Kindsvater Fusion architectures for multimodal affect recognition under real time conditions, Master Arbeit, 05/2016
• Christian Speck Entwicklung personalisierter Mehrklassifikatorensysteme, Master Arbeit, 05/2016
• Heinke Hihn Inferring Affective State from Postural Behaviour and Gestures with Ensemble Methods, Master Arbeit, 04/2016
• Mehmet Erdal Emotionserkennung in gesprochener Sprache mit Deep Learning Architekturen, Master Arbeit, 07/2015
• Viktor Kessler Videobasierte Schätzung von EKG-Signalen, Master Arbeit, 03/2015
• Vera Müller Ensemblemethoden zur Clusteranalyse von Multi-Instanz Anwendungen zur Erstellung von Nutzerprofilen, Master Arbeit, 08/2014
• Patrick Thiam Novelty Detection in a HCI Scenario utilizing Active Learning Algorithms, Master Arbeit, 07/2014
• Thomas Reckow Deep Learning Architectures for Audio-Visual Emotion Recognition, Master Arbeit, 05/2014
• Andrej Schwarz Audio-visuelle Personenerkennung, Diplom Arbeit, 03/2014
• Josef Frick Emotionserkennung in gesprochener Sprache mit neuronalen Netzen, Master Arbeit, 03/2014
• Robert Retz Active Multi-Instance Multi-Label Learning, Master Arbeit, 03/2014
• Dimitry Zharkov Analysis and Fusion of Voice Quality Features for Automatic Emotion Recognition, Master Arbeit, 10/2013
• Manuel Meder Speaker clustering and classification from speech, Master Arbeit, 07/2013
• Robert Böser Partiell überwachtes Lernen zur Erkennung von Emotionen aus gesprochener Sprache, Master Arbeit, 09/2012
• Igor Arndt Aktive Lernverfahren für Mehr-Klassifikator-Systeme zur Emotionserkennung, Master Arbeit, 07/2012
   
• Individualpraktikum: ATLAS (2013-2014)
• Praktikum/Projekt: Neuroinformatik - Sprecheridentifikation (2010-2013)

• AI CON 2018, Bosch Center for Artificial Intelligence, Renningen (Germany), Oktober 2018
   
• MakerCon 2017, from Maker to Market, Heidelberg (Germany), Februar 2017
   
• Nvidia Deep Learning HPC event, München (Germany), Februar 2017
   
• Pain Face Day, Challenges of Automatic Pain Recognition, Erlangen (Germany), Januar 2017
   
• 23rd IAPR International Conference on Pattern Recognition (ICPR 2016) and 4th International Workshop on Multimodal Pattern Recognition of Social Signals in human computer interaction (MPRSS 2016), Cancun (Mexico), Dezember 2016
   
• 18th ACM International Conference on Multimodal Interaction (ICMI 2016) and 2nd International Workshop on Emotion Representations and Modelling for Companion Systems (ERM4CT 2016), Tokyo (Japan), November 2016
   
• 7th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR'16), Ulm (Germany), September 2016
   
• 2015 IEEE Symposium Series on Computational Intelligence (SSCI 2015) and 2015 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2015), Kapstadt (Südafrika), Dezember 2015
   

• 12th International Workshop on Multiple Classifier Systems (MCS 2015), Günzburg (Germany), Juni 2015

• 16th ACM International Conference on Multimodal Interaction (ICMI 2014) and 2nd Emotion Recognition in the Wild Challenge and Workshop (EmotiW 2014) and 2nd International Workshop on Emotion Representations and Modelling for HCI Systems (ERM4HCI 2014), Istanbul (Turkey), November 2014

• 6th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR'14), Montreal (Canada), October 2014

• 2nd European Conference on Data Analysis (ECDA 2014), Bremen (Germany), July 2014

• International Research Stay at the Vision and Sensing Research Group at the Faculty of Education, Science, Technology and Mathematics at the University of Canberra, Canberra (Australia), December 2013

• 15th ACM International Conference on Multimodal Interaction (ICMI 2013) and 1st Emotion Recognition in the Wild Challenge and Workshop (EmotiW 2013), Sydney (Australia), December 2013

• 13th International Conference on Intelligent Virtual Agents (IVA 2013) and 1st International Workshop on Techniques Towards Companion Technologies (T2CT 2013), Edinburgh (Scotland - UK), August 2013

• 1st interdisciplinary meeting for the study of pain of the Federal University of Uberlândia (ENID-UFU 2013), Uberlândia (Brazil), July 2013

• 45th Workshop on Statistical Computing, Castle Reisensburg, Günzburg (Germany) June 2013

• IEEE International Conference on Cybernetics (CYBCONF 2013) and 2nd International Workshop on Multimodal pattern recognition of social signals in human computer interaction (MPRSS 2013), Lausanne (Switzerland), June 2013

• IEEE International Conference on Robotics and Automation (ICRA 2013), Karlsruhe (Germany), May 2013

• 5th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR'12), Trento (Italy), September 2012

• International Conference on Affective and Pleasurable Design (APD'12) [Jointly with the 4th International Conference on Applied Human Factors and Ergonomics (AHFE'12)], San Francisco (CA - USA), July 2012

• IAPR TC3 Workshop on Partially Supervised Learning (PSL 2011), Ulm (Germany), September 2011

• S. Meudt: "Maschinelle Emotionserkennung in der Mensch-Maschine Interaktion." 2019
   
• V. Srinivasan, S. Meudt, F. Schwenker: "Deep Learning Algorithms for Emotion Recognition on Low Power Single Board Computers." In: IAPR Workshop on Multimodal Pattern Recognition of Social Signals in Human-Computer Interaction (MPRSS), 2018, pp. 59-70
   
• P. Thiam, S. Meudt, G. Palm, and F. Schwenker: "A Temporal Dependency Based Multi-modal Active Learning Approach for Audiovisual Event Detection" In: Neural Processing Letters, 2017, DOI: 10.1007/s11063–017–9719–y , ISSN: 1573–773X
   
• D. Kindsvater, S. Meudt and F. Schwenker "Fusion Architectures for Multimodal Cognitive Load Recognition" in Proceedings of the 4th International Workshop on Multimodal pattern recognition of social signals in human computer interaction (MPRSS'16), 2016, pp. 1-8
   
• D. Held, S. Meudt and F. Schwenker "Bimodal recognition of Cognitive Load based on Speech and Physiological changes" in Proceedings of the 4th International Workshop on Multimodal pattern recognition of social signals in human computer interaction (MPRSS'16), 2017, pp. 1-8 
   
• H. Hihn, S. Meudt and F. Schwenker "Inferring mental overload based on postural behavior and gestures", in Proceedings of the 2nd workshop on Emotion Representation and Modeling for Companion Systems (ERM4CT'16), 2016, pp. 1-4
   
• P. Thiam, S. Meudt, F. Schwenker and G.Palm "Active Learning for Speech Event Detection in HCI", in Proceedings of Artificial Neural Networks in Pattern Recognition (ANNPR'16), 2016, pp. 285-297
   
• H. Hihn, S. Meudt and F. Schwenker "On Gesture and Postural Behavior as a Modality in Ensamble Methods", in Proceedings of Artificial Neural Networks in Pattern Recognition (ANNPR'16), 2016, pp. 312-323
   
• M. Valena, S. Gruss, G. Layher, P. Thiam, Y. Zhang, D. Schork, V. Kessler, S. Meudt, H. Neumann, J. Kim, F. Schwenker, E. Andre, H. C. Traue, S. Walter "The SenseEmotion Database: A Multimodal Database for the Development and Systematic Validation of an Automatic Pain and Emotion-Recognition System." in Proceedings of Artificial Neural Networks in Pattern Recognition (ANNPR'16), 2016, pp. 127-139
   
• V. Kessler, M. Kächele, S. Meudt, F. Schwenker and G.Palm "Machine Learning Driveb Heart Rate Detection with Camera Photoplethysmography in Time Domain", in Proceedings of Artificial Neural Networks in Pattern Recognition (ANNPR'16), 2016, pp. 324-334
   
• S. Meudt, M. Schmidt-Wack, F. Honold, F. Schüssel, M. Weber, F. Schwenker and G. Palm "Going Further in Affective Computing: How Emotion Recognition Can Improve Adaptive User Interaction", in Toward Robotic Socially Believable Behaving Systems: Modeling Emotions -- Volume I , 2016, pp.73-103, ISBN: 978-3-319-31055-8, doi 10.1007/978-3-319-31056-5_6

• M. Kächele, M. Schels, S. Meudt, G. Palm, and F. Schwenker "Revisiting the EmotiW challenge: how wild is it really?", in Journal on Multimodal User Interfaces , 2016, pp. 1-12

• F. Schwenker, R. Böck, M. Schels, S. Meudt, I. Siegert, M. Glodek, M. Kächele, M. Schmidt-Wack, P. Thiam, A. Wendemuth, G. Krell"Multimodal Affect Recognition in the Context of Human-Computer Interaction for Companion Systems", in Companion Technology, 2016

• S. Meudt, I. Siegert, F. Schüssel, M. Schmidt, S. Reuter, G. Layher, G. Krell, T. Hörnle, S. Handrich, A. Al-Hamadi, K. Dietmayer, H. Neumann, G. Palm, F. Schwenker, A. Wendemuth "Multi-Modal Information Processing in Companion Systems—A Ticket Purchase System", in Companion Technology, 2016

• I. Siegert, S. Reuther, F. Schüssel, G. Layher, T. Hörnle, S. Meudt, A. Wendemuth "Multimodal Information Processing: The Ticket Purchase - a Demonstration Scenario of the SFB/TRR-62", in Elektronische Sprachsignalverarbeitung 2016, 2016, pp.111-118

• S. Meudt and F. Schwenker "ATLAS - Machine learning based annnotation of multimodal data recorded in human-computer interaction scenarios", in Proceedings of the 1st International Symposium on Companion-Technology (ISCT 2015), 2015, pp.181-186

• M. Kächele, M. Schels, S. Meudt, V. Kessler, M. Glodek, P. Thiam, S. Tschechne, G. Palm, and F. Schwenker "On Annotation and Evaluation of Multi-modal Corpora in Affective Human-Computer Interaction.", in Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction, Lecture Notes in Computer Science, 2015, pp.35-44

• P. Thiam, S. Meudt, M. Kächele and F. Schwenker, "Detection of Emotional Events Utilizing Support Vector Methods in an Active Learning HCI Scenario", in Proceedings of the 2014 Workshop on Emotion Representation and Modeling in Human Computer Interaction Systems (ERM4HCI'14), 2014, pp.31-36, ISBN: 978-1-4503-0124-4, doi 10.1145/2668056.2668062

• S. Meudt and F. Schwenker, "Enhanced Autocorrelation in Real World Emotion Recognition", in Proceedings of the 16th International conference on multimodal interaction (ICMI'14), 2014, pp.502-507, ISBN: 978-1-4503-2885-2, doi 10.1145/2663204.2666276

• F. Schwenker, M. Frey, M. Glodek, M. Kächele, S. Meudt, M. Schels, and M. Schmidt, "A new multi-class fuzzy support vector machine algorithm.", in Proceedings of Artificial Neural Networks in Pattern Recognition (ANNPR'14), 2014, pp. 153-164

• M. Kächele, M. Schels, S. Meudt, V. Kessler, M. Glodek, P. Thiam, S. Tschechne, G. Palm and F. Schwenker, "On Annotation and Evaluation of Multi-Modal Corpora in Affective Human-Computer Interaction.", in Proceedings of Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction (MA3HMI'14), 2014

• M. Kächele, M. Glodek, D. Zharkov, S. Meudt and F. Schwenker, "Fusion of audio-visual features using hierarchical classifier systemsfor the recognition of affective states and the state of depression", in Proceedings of the International Conference on Pattern Recognition Applications and Methods (ICPRAM), 2014

• S. Meudt, D. Zharkov, M. Kächele and F. Schwenker, "Multi Classifier Systems and Forward Backward Feature Selection Algorithms to Classify Emotional Coloured Speech", in Proceedings of the 15th ACM on International conference on multimodal interaction (ICMI'13), 2013, pp. 551-556, ISBN: 978-1-4503-2129-7, doi 10.1145/2522848.2531743

• D. Zharkov, M. Kächele, S.Meudt, and F. Schwenker, "A long-term stopping criterion for the forward-backward feature selection algorithm for the classification of emotions in speech", in Joint Proceedings of the 2013th T2CT and CCGL Workshops at IVA 2013, Edinburgh, UK, 2013, pp. 25-33. ISBN: 978­3­940961­99­0

• M. Frey, M. Schels, M. Glodek, S. Meudt, M. Kächele and F. Schwenker, "Investigation of fuzzy support vector machines", in Proceedings of the Statistical Computing 2013, Castle Reisensburg, Günzburg, Germany, 2013, pp. 17-17.

• S. Meudt, M. Glodek, M. Schels and F. Schwenker, "Multi-view video based tracking and audio-visual identification of persons in a human-computer-interaction scenario", in Proceedings of IEEE International Conference on Cybernetics (CybConf'13), Lausanne, Switzerland, 2013

• M. Schels, M. Glodek, S. Meudt, S. Scherer, M. Schmidt, G. Layher, S. Tschechne, T. Brosch, D. Hrabal, S. Walter, H. Traue, G. Palm, H. Neumann and F. Schwenker, "Multi-modal classifier-fusion for the recognition of emotions", in Coverbal Synchrony in Human-Machine Interaction, 1st ed., M. Rojc and N. Campbell, Eds. CRC Press, 2013, pp. 73-98.

• S. Meudt and F. Schwenker, "On instance selection in audio based emotion recognition", in Proceedings of the 5th IAPR TC3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'12), Trento, Italy, 2012, pp. 186-192.

• S. Meudt, L. Bigalke and F. Schwenker, "ATLAS – an annotation tool for HCI data utilizing machine learning methods", in Proceedings of the 1st International Conference on Affective and Pleasurable Design (APD'12) [Jointly with the 4th International Conference on Applied Human Factors and Ergonomics (AHFE'12)], 2012, pp. 5347-5352.

• S. Meudt, L. Bigalke and F. Schwenker, "ATLAS - annotation tool using partially supervised learning and multi-view co-learning in human-computer-interaction scenarios", in Proceedings of the 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA'12), 2012, pp. 1309-1312.

• M. Schels, M. Glodek, S. Meudt, M. Schmidt, D. Hrabal, R. Böck, S. Walter and F. Schwenker, "Multi-modal classifier-fusion for the classification of emotional states in WOZ scenarios", in Proceedings of the 1st International Conference on Affective and Pleasurable Design (APD'12) [Jointly with the 4th International Conference on Applied Human Factors and Ergonomics (AHFE'12)], 2012, pp. 5337-5346.

• F. Schwenker and S. Meudt, "On instance selection in multiple classifier systems", in Proceedings of the 36th Annual Conference of the German Classification Society (GfKl'12), Hildesheim, Germany, 2012, pp. 50.

• S. Scherer, I. Siegert, L. Bigalke and S. Meudt, "Developing an expressive speech labeling tool incorporating the temporal characteristics of emotion", in Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), 2010, pp. 1172-1175.