Dr. Burkhard Hoppenstedt
Burkhard Hoppenstedt studierte Medieninformatik an der Universität Ulm und der NTNU (Trondheim, Norwegen). Er schloss seinen Master im Jahr 2016 ab. In seiner Masterarbeit, die in Kooperation mit der ATR Software GmbH durchgeführt wurde, beschäftigte er sich mit der Produktionsüberwachung in der Industrie anhand der OEE-Kennzahl sowie der vorausschauenden Wartung (Predictive Maintenance).
In seiner Funktion als externer Doktorand wird er sich mit Modellen und Vorgehensweisen aus dem Bereich des Predictive Analytics im industriellen Kontext (Industrie 4.0) beschäftigen.
Seine Freizeit verbringt er damit in 80 Tagen um die Welt zu reisen, Theater zu improvisieren und seinen cineastischen Horizont zu erweitern.
Forschungsinteressen
- Outlier Detection
- Predictive Maintenance
- Data Visualization
Projekte
| 2020 | 2019 | 2018 | 2017 |
2020
| Hoppenstedt, Burkhard and Reichert, Manfred and El-Khawaga, Ghada and Winter, Karl-Michael and Pryss, Rüdiger (2020) Detecting Production Phases Based on Sensor Values using 1D-CNNs. arXiv. |  |
| Hoppenstedt, Burkhard and Probst, Thomas and Reichert, Manfred and Schlee, Winfried and Kammerer, Klaus and Spiliopoulou, Myra and Schobel, Johannes and Winter, Michael and Felnhofer, Anna and Kothgassner, Oswald and Pryss, Rüdiger (2020) Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios. Journal of Visualized Experiments (JoVE), 164(e61349), J. Vis. Exp., 10.3791/61349. |
| Kammerer, Klaus and Pryss, Rüdiger and Hoppenstedt, Burkhard and Sommer, Kevin and Reichert, Manfred (2020) Process-Driven and Flow-Based Processing of Industrial Sensor Data. Sensors, 20(18), MDPI, 10.3390/s20185245. | |
| Pryss, Rüdiger and Schlee, Winfried and Hoppenstedt, Burkhard and Reichert, Manfred and Spiliopoulou, Myra and Langguth, Berthold and Breitmayer, Marius and Probst, Thomas (2020) Applying Machine Learning to Daily-Life Data From the TrackYourTinnitus Mobile Health Crowdsensing Platform to Predict the Mobile Operating System Used With High Accuracy: Longitudinal Observational Study. J Med Internet Res, 22(6), JMIR. | |
2019
| Hoppenstedt, Burkhard and Reichert, Manfred and Kammerer, Klaus and Spiliopoulou, Myra and Pryss, Rüdiger (2019) Towards a Hierarchical Approach for Outlier Detection in Industrial Production Settings. In: EDBT/ICDT 2019 Workshops, Lisbon, 26 March 2019, CEUR Workshop Proceedings 2322, CEUR-WS.org. | |
| Hoppenstedt, Burkhard and Kammerer, Klaus and Reichert, Manfred and Spiliopoulou, Myra and Pryss, Rüdiger (2019) Convolutional Neural Networks for Image Recognition in Mixed Reality Using Voice Command Labeling. In: 6th International Conference on Augmented Reality, Virtual Reality and Computer Graphics (SALENTO AVR 2019), Santa Maria al Bagno, Italy, June 24-27, 2019, Lecture Notes in Computer Science 11614, Springer, pp. 63-70. | |
| Hoppenstedt, Burkhard and Schmid, Michael and Kammerer, Klaus and Scholta, Joachim and Reichert, Manfred and Pryss, Rüdiger (2019) Analysis of Fuel Cells Utilizing Mixed Reality and IoT Achievements. In: 6th International Conference on Augmented Reality, Virtual Reality and Computer Graphics (SALENTO AVR 2019), Santa Maria al Bagno, Italy, June 24-27, 2019, Lecture Notes in Computer Science 11614, Springer, pp. 371-378. | |
| Hoppenstedt, Burkhard and Witte, Thomas and Ruof, Jona and Kammerer, Klaus and Tichy, Matthias and Reichert, Manfred and Pryss, Rüdiger (2019) Debugging Quadrocopter Trajectories in Mixed Reality. In: 6th International Conference on Augmented Reality, Virtual Reality and Computer Graphics (SALENTO AVR 2019), Santa Maria al Bagno, Italy, June 24-27, 2019, Lecture Notes in Computer Science 11614, Springer, pp. 43-50. | |
| Hoppenstedt, Burkhard and Probst, Thomas and Reichert, Manfred and Schlee, Winfried and Kammerer, Klaus and Spiliopoulou, Myra and Schobel, Johannes and Winter, Michael and Felnhofer, Anna and Kothgassner, Oswald and Pryss, Rüdiger (2019) Applicability of Immersive Analytics in Mixed Reality: Usability Study . IEEE Access, Vol. 7, pp. 71921-71932, 10.1109/ACCESS.2019.2919162. | |
| Hoppenstedt, Burkhard and Reichert, Manfred and Kammerer, Klaus and Probst, Thomas and Schlee, Winfried and Spiliopoulou, Myra and Pryss, Rüdiger (2019) Dimensionality Reduction and Subspace Clustering in Mixed Reality for Condition Monitoring of High-Dimensional Production Data. Sensors, MDPI, Vol. 19, pp. 3303, 10.3390/s19183903. | |
| Kammerer, Klaus and Hoppenstedt, Burkhard and Pryss, Rüdiger and Stökler, Steffen and Allgaier, Johannes and Reichert, Manfred (2019) Anomaly Detections for Manufacturing Systems Based on Sensor DataInsights into Two Challenging Real-World Production Settings. Sensors, 19(24), MDPI, 10.3390/s19245370. | |
| Pryss, Rüdiger and Schlee, Winfried and Reichert, Manfred and Kurthen, Ira and Giroud, Nathalie and Jagoda, Laura and Neuschwander, Pia and Meyer, Martin and Neff, Patrick and Schobel, Johannes and Hoppenstedt, Burkhard and Spiliopoulou, Myra and Langguth, Berthold and Probst, Thomas (2019) Ecological Momentary Assessment based Differences between Android and iOS Users of the TrackYourHearing mHealth Crowdsensing Platform. In: 41st International Engineering in Medicine and Biology Conference, Berlin, Germany, July 2327, 2019, IEEE Computer Society Press, pp. 3951-3955. | |
| Pryss, Rüdiger and John, Dennis and Reichert, Manfred and Hoppenstedt, Burkhard and Schmid, Lukas and Schlee, Winfried and Spiliopolou, Myra and Schobel, Johannes and Kraft, Robin and Schickler, Marc and Langguth, Berthold and Probst, Thomas (2019) Machine Learning Findings on Geospatial Data of Users from the TrackYourStress mHealth Crowdsensing Platform. In: IEEE 20th International Conference on Information Reuse and Integration for Data Science (IRI 2019), Los Angeles, California, USA, July 30 - August 1, 2019, IEEE Computer Society Press, pp. 350-355. | |
2018
| Hoppenstedt, Burkhard and Schneider, Christian and Pryss, Rüdiger and Schlee, Winfried and Probst, Thomas and Neff, Patrick and Simoes, Jorge and Treß, Alexander and Reichert, Manfred (2018) HOLOVIEW: Exploring Patient Data in Mixed Reality. In: TRI / TINNET Conference 2018 , Regensburg. | |
| Hoppenstedt, Burkhard and Pryss, Rüdiger and Stelzer, Birgit and Meyer-Brötz, Fabian and Kammerer, Klaus and Treß, Alexander and Reichert, Manfred (2018) Techniques and Emerging Trends for State of the Art Equipment Maintenance Systems - A Bibliometric Analysis . Applied Sciences, MDPI, Vol. 8, pp. 1-29, 10.3390/app8060916. | |
| Hoppenstedt, Burkhard and Reichert, Manfred and Schneider, Christian and Kammerer, Klaus and Schlee, Winfried and Probst, Thomas and Langguth, Berthold and Pryss, Rüdiger (2018) Exploring Dimensionality Reduction Effects in Mixed Reality for Analyzing Tinnitus Patient Data. In: 4th Int'l Conference of the Virtual and Augmented Reality in Education (VARE 2018), Budapest, Hungary, 17 - 19 September 2018, pp. 163-170. | |
| Hoppenstedt, Burkhard and Pryss, Rüdiger and Kammerer, Klaus and Reichert, Manfred (2018) CONSENSORS: A Neural Network Framework for Sensor Data Analysis. In: OTM 2018 Workshops, Valetta, Malta, October 22-26, LNCS 11231, Springer, pp. 196-200. | |
2017
| Hoppenstedt, Burkhard and Pryss, Rüdiger and Treß, Alexander and Biechele, Bernd and Reichert, Manfred (2017) Datengetriebene Module für Predictive Maintenance. ProductivITy, Vol. 22, pp. 21-23. | |
Frankfurter Entwicklertag 2017:
Der Funke springt über - Apache Spark in einem Raspberry Cluster
IoT - Vom Sensor in die Cloud 2017:
Eine MQQT basierte Architektur für Neuronale Netze
| 2020 | 2019 | 2018 | 2017 | 2016 |
2020
| Buck, Timo (2020) Deep Learning in the Context of Inventory Valuation in the Pharmaceutical Industry. Master thesis, Ulm University. | |
| Henkel, Fabian (2020) Generische UI-Konzepte im Web-Frontend. Master thesis, Institute of Databases and Informations Systems. | |
2019
| Allgaier, Johannes (2019) Machine learning under concept drift for industrial data using Python. Master thesis, Institute of Databases and Informations Systems. | |
| Berroth, Kai-Uwe (2019) Evaluation von Vorhersagemodellen auf Basis von UN Millenniumszielen. Master thesis, Institute of Databases and Informations Systems. | |
| Wochele, Joel (2019) Evaluation von Angular Elements im Kontext von Produktionsleitsystemen mittels einer Microservice-Architektur. Master thesis, Ulm University. | |
2018
| Hesse, Lukas (2018) Modellgetriebene Softwareentwicklung im Umfeld von Manufacturing Execution Systems. Master thesis, Ulm University. | |
| Hunt, Alexander (2018) Vision Enhancement for Autonomous Driving under Adverse Weather Conditions using Generative Adversarial Nets. Master thesis, Ulm University. | |
| Tong, Yu (2018) Path Recognition with DTW in a Distributed Environment. Master thesis, Ulm University. | |
| Väth, Thomas (2018) Exploring Temporal Data in a Mixed-Reality Application. Bachelor thesis, Ulm University. | |
2017
| Grabiec, Sebastian (2017) Developing a client-specific workflow for Predictive Maintenance. Master thesis, Ulm University. | |
| Grausz, Krisztián (2017) Log Analyzer for IoT Applications. Master thesis, Ulm University. | |
| Kuhaupt, Nicolas (2017) Conception And Analysis Of A Raspberry Pi Cluster With Apache Spark. Master thesis, Ulm University. | |
| Salonikidis, Georgios (2017) Minimization of Redundant Make-To-Stock Production in a Dental Factory: An Integer Linear Programming Approach. Bachelor thesis, Ulm University. | |
| Schwarz, Holger (2017) Evaluierung neuronaler Netze auf Maschinendatenbasis. Master thesis, Ulm University. | |
2016
| Ipekbayrak, Gözde (2016) Using NoSQL Databases in the Context of Manufacturing Execution Systems. Master thesis, Ulm University. | |
| Reutlinger, Jürgen (2016) Einsatz von Prozess Management Technologie in Manufacturing Execution Systems. Master thesis, Ulm University. | |
| Wagner, Eugen (2016) Microservices as a Manufacturing Execution System Architecture. Master thesis, Ulm University. | |
Kontakt
Dr. Burkhard Hoppenstedt
Wissenschaftl. Mitarbeiter
Büro: Geb. O27 - Raum 5203
Sprechzeiten nach Vereinbarung.
burkhard.hoppenstedt(at)uni-ulm.de
| Telefon: | +49 731 50 24 136 |
| Fax: | +49 731 50 24 134 |