Person hält übergroßen Doktorhut in einer feierlichen Umgebung hoch. ITIV

M. Sc. Marco Stang

  • Corrector: Prof. Dr. rer. nat. Cornelius Neumann

Summary of the dissertation

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Self-learning systems that adapt their behavior individually to users during operation are becoming increasingly relevant - for example in vehicles that remember personal driving habits.

However, the validation of such dynamically learning functions poses considerable challenges for conventional test procedures.

This dissertation therefore presents a novel validation approach that combines realistic usage scenarios with intelligent test methods in order to test the behavior of self-adaptive systems in a targeted and comprehensible manner.

We would like to congratulate Marco Stang on this significant achievement and wish him all the best for his scientific and professional future.

Publications


2025
PhD Theses
2024
Conference Papers
Exploring Metamorphic Testing for Self-learning Functions with User Interactions
Stang, M.; Seidel, L.; Vučinić, V.; Sax, E.
2024. Human Interaction and Emerging Technologies (IHIET 2024), 195–206, AHFE International. doi:10.54941/ahfe1004569
USID - Unsupervised Identification of the Driver for Vehicle Comfort Functions
Vučinić, V.; Seidel, L.; Stang, M.; Sax, E.
2024. Human Interaction and Emerging Technologies (IHIET-AI 2024): Artificial Intelligence and Future Applications, 142–152, AHFE International. doi:10.54941/ahfe1004564
2023
Conference Papers
Context-Aware Policy for Route Planning and Feasible Vehicle Technologies
Kraus, D.; Junk, C.; Stang, M.; Sax, E.
2023. 2023 IEEE International Automated Vehicle Validation Conference (IAVVC), 6 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IAVVC57316.2023.10328101
Unraveling Scenario-Based Behavior of a Self-Learning Function with User Interaction
Stang, M.; Schindewolf, M.; Sax, E.
2023. Human Interaction and Emerging Technologies (IHIET 2023): Artificial Intelligence and Future Applications. Ed.: T. Ahram, AHFE International. doi:10.54941/ahfe1004028
2022
Conference Papers
Development of a self-learning automotive comfort function: an adaptive gesture control with few-shot-learning
Stang, M.; Stock, S.; Müller, S.; Sax, E.; Stork, W.
2022. 2022 International Conference on Connected Vehicle and Expo (ICCVE), 1–8, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICCVE52871.2022.9742989
2021
Book Chapters
CAGEN - Context-Action Generation for Testing Self-learning Functions
Stang, M.; Marquez, M. G.; Sax, E.
2021. Human Interaction, Emerging Technologies and Future Applications IV – Proceedings of the 4th International Conference on Human Interaction and Emerging Technologies: Future Applications (IHIET – AI 2021), April 28-30, 2021, Strasbourg, France. Ed.: T. Ahram, 12–19, Springer International Publishing. doi:10.1007/978-3-030-74009-2_2
Acceptance of Smart Automated Comfort Functionalities in Vehicles
Guinea, M.; Stang, M.; Nitsche, I.; Sax, E.
2021. Human Interaction, Emerging Technologies and Future Applications IV – Proceedings of the 4th International Conference on Human Interaction and Emerging Technologies: Future Applications (IHIET – AI 2021), April 28-30, 2021, Strasbourg, France. Ed.: T. Ahram, 331–338, Springer International Publishing. doi:10.1007/978-3-030-74009-2_42
Journal Articles
Context-aware Security for Vehicles and Fleets: A Survey
Grimm, D.; Stang, M.; Sax, E.
2021. IEEE Access, 9, 101809–101846. doi:10.1109/ACCESS.2021.3097146
Conference Papers
Introduction of an Algorithm Based on Convolutional Neural Networks for an Automated Online Correction of Braided Cardiovascular Implants
Haas, B.; Stang, M.; Khan-Blouki, V.; Sax, E.
2021. Human Interaction, Emerging Technologies and Future Applications IV. Ed.: T. Ahram, 28–36, Springer International Publishing. doi:10.1007/978-3-030-74009-2_4
Audio & Video
K-Means-Clustering
Molinar, G.; Stang, M.
2021. doi:10.5445/IR/1000139095
2020
Book Chapters
Adaptive Customized Forward Collision Warning System Through Driver Monitoring
Stang, M.; Sommer, M.; Baumann, D.; Zijia, Y.; Sax, E.
2020. Proceedings of the Future Technologies Conference (FTC) 2020, Volume 2. Ed.: K. Arai, 757–772, Springer International Publishing. doi:10.1007/978-3-030-63089-8_50
Conference Papers
Evaluation of Deep Reinforcement Learning Algorithms for Autonomous Driving
Stang, M.; Grimm, D.; Gaiser, M.; Sax, E.
2020. 2020 IEEE Intelligent Vehicles Symposium (IV), 19 October - 13 November 2020, online, 1576–1582, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IV47402.2020.9304792
QUA³CK - A Machine Learning Development Process
Stock, S. C.; Becker, J.; Grimm, D.; Hotfilter, T.; Molinar, G.; Stang, M.; Stork, W.
2020. Proceedings of Artificial Intelligence for Science, Industry and Society — PoS(AISIS2019), 026, Scuola Internazionale Superiore di Studi Avanzati (SISSA). doi:10.22323/1.372.0026
TalkyCars: A Distributed Software Platform for Cooperative Perception among Connected Autonomous Vehicles based on Cellular-V2X Communication
Sommer, M.; Stang, M.; Muetsch. Ferdinand; Sax, E.
2020. IEEE Intelligent Vehicles Symposium, October 19 - November 13, 2020, (Virtual) Las Vegas, NV
FEEDI - A Smart Wearable Foot-Band for Navigation and Guidance Using Haptic Feedback
Stock, S.; Bertemes, A.; Stang, M.; Böhme, M.; Grimm, D.; Stork, W.
2020. Human Interaction, Emerging Technologies and Future Applications II : Proceedings of the 2nd International Conference on Human Interaction and Emerging Technologies: Future Applications (IHIET – AI 2020), April 23-25, 2020, Lausanne, Switzerland. Ed.: T. Ahram, 349–355, Springer. doi:10.1007/978-3-030-44267-5_52
An Evolutionary Approach to Hyper-Parameter Optimization of Neural Networks
Stang, M.; Meier, C.; Rau, V.; Sax, E.
2020. Human Interaction and Emerging Technologies. Ed.: T. Ahram, 713–718, Springer International Publishing. doi:10.1007/978-3-030-25629-6_111
Using Machine Learning to Optimize Energy Consumption of HVAC Systems in Vehicles
Böhme, M.; Lauber, A.; Stang, M.; Pan, L.; Sax, E.
2020. Human Interaction and Emerging Technologies. Ed.: T. Ahram, 706–712, Springer International Publishing. doi:10.1007/978-3-030-25629-6_110
2019
Conference Papers
Applied Machine Learning: Reconstruction of Spectral Data for the Classification of Oil-Quality Levels
Stang, M.; Böhme, M.; Sax, E.
2019. 5th International Conference on Research in Engineering, Technology and Science (ICRETS 2019), Lissabon, P, February 3-7, 2019, 1–13, ISRES Publishing
Presentations
The QUA³CK Machine Learning Development Process and the Laboratory for Applied Machine Learning Approaches (LAMA)
Becker, J.; Grimm, D.; Hotfilter, T.; Meier, C.; Molinar, G.; Stang, M.; Stock, S.; Stork, W.
2019, October 22. Symposium Artificial Intelligence for Science, Industry and Society (AISIS 2019), Mexico City, Mexico, October 20–December 25, 2019