Journals:

• S. Reitmann, T. Mihaylova, D. Kritharoulas, E. Peltola, E.A. Topp and V. Kyrki. “Beep and Show, Don’t Tell: Multimodal Feedback Strategies for Driver-Automation Coordination in Critical Driving Situations”. In: Computers. 2026, 15, 516. https://doi.org/10.3390/computers15080516

• S. Pose, S. Reitmann, G. J. Licht, T. Grab and T. Fieback. “AI-Prepared Autonomous Freshwater Monitoring and Sea Ground Detection by an Autonomous Surface Vehicle”. In: Remote Sensing. 2023; 15(3):860. DOI: 10.3390/rs15030860. URL: https://www.mdpi.com/2114402

• S. Reitmann, M. Schultz. “An Adaptive Framework for Optimization and Prediction of Air Traffic Management (Sub-)Systems with Machine Learning”. In: Aerospace. 2022; 9(2):77. DOI: 10.3390/aerospace9020077. URL: https://www.mdpi.com/2226-4310/9/2/77

• S. Reitmann, B. Jung, E. V. Kudryashova and V. Reitmann. “Observation Stability and Convergence for Neural-type Evolutionary Variational Inequalities”. In: Differential Equations and Control Processes N.2 (2021). ISSN: 1817-2172. URL: https://diffjournal.spbu.ru/pdf/21208-jdecp-reitmann.pdf

• S. Reitmann, L. Neumann and B. Jung. “BLAINDER—A Blender AI Add-On for Generation of Semantically Labeled Depth-Sensing Data”. In: Sensors 21.6 (2021). ISSN: 1424-8220. DOI: 10.3390/s21062144. URL: https://www.mdpi.com/1424-8220/21/6/2144.

• M. Schultz, S. Reitmann and S. Alam, “Predictive classification and understanding of weather impact on airport performance through machine learning”. In: Transportation Research Part C: Emerging Technologies 131 (2021), S. 103-119, ISSN 0968-090X, DOI: https://doi.org/10.1016/j.trc.2021.103119.

• M. Schultz and S. Reitmann. “Machine learning approach to predict aircraft boarding”. In: Transportation Research Part C: Emerging Technologies 98 (Jan. 2019), S. 391–408. ISSN: 0968-090X. DOI: 10.1016/j.trc.2018.09.007. URL: http://www.sciencedirect.com/science/article/pii/S0968090X18312580.

• M. Schultz and S. Reitmann. “Consideration of Passenger Interactions for the Prediction of Aircraft Boarding Time”. In: Aerospace 5.4 (Sep. 2018), S. 101. DOI: 10.3390/aerospace5040101. URL: https://www.mdpi.com/2226-4310/5/4/101.

Conference Proceedings:

• Maben, R.P. et al. (2027). Towards Intent-Aware Human-Robot Teaming: A Platform for Search-and-Rescue Operations. In: Lorig, F., Davidsson, P., Klügl, F., Camps, V., Nieves Sanchez, J.C., Kaddoum, E. (eds) Multi-Agent Systems. EUMAS 2026. Lecture Notes in Computer Science(), vol 16829. Springer, Cham. https://doi.org/10.1007/978-3-032-39395-1_39

• Jena, A., Reitmann, S., Topp, E.A. (2026). Impact of Gaze-Based Interaction and Augmentation on Human-Robot Collaboration in Critical Tasks. In: Staffa, M., et al. Social Robotics + AI. ICSR+AI 2025. Lecture Notes in Computer Science(), vol 16131. Springer, Singapore. https://doi.org/10.1007/978-981-95-2379-5_52

• T. Mihaylova, S. Reitmann, E. A. Topp and V. Kyrki, “Injecting Conflict Situations in Autonomous Driving Simulation Using CARLA,” 2025 20th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Melbourne, Australia, 2025, pp. 1052-1056, doi: 10.1109/HRI61500.2025.10974213.

• Rohith Prem Maben, Ayesha Jena, Stefan Reitmann, and Elin Anna Topp. 2025. “Framework for Assessing Situational Awareness in Beyond Visual Line of Sight UAV Operations”. In Proceedings of the 2025 ACM/IEEE International Conference on Human-Robot Interaction (HRI ‘25). IEEE Press, 1473–1477.

• Tsvetomila Mihaylova, Stefan Reitmann, Elin A. Topp, and Ville Kyrki. 2025. “Injecting Conflict Situations in Autonomous Driving Simulation using CARLA”. In Proceedings of the 2025 ACM/IEEE International Conference on Human-Robot Interaction (HRI ‘25). IEEE Press, 1052–1056.

• F. Heisel, L. Kulke, Z. Beek, S. Reitmann, and B. Pfleging. 2024. “Pedestrian-Robot Interaction on Sidewalks: External User Interfaces for Mobile Delivery Robots”. In Proceedings of the International Conference on Mobile and Ubiquitous Multimedia (MUM ‘24). Association for Computing Machinery, New York, NY, USA, 365–380. https://doi.org/10.1145/3701571.3701581

• S. Reitmann and B. Jung. 2024. “VR-based Assistance System for Semi-Autonomous Robotic Boats”. In Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’24 Companion), March 11–14, 2024, Boulder, CO, USA. ACM, New York, NY, USA, 5 pages. URL: https://doi.org/10.1145/3610978.3640750

• S. Reitmann, T. Mihaylova, E. A. Topp, and V. Kyrki. 2024. “Conflict Simulation for Shared Autonomy in Autonomous Driving”. In Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’24 Companion), March 11–14, 2024, Boulder, CO, USA. ACM, New York, NY, USA, 6 pages. URL: https://doi.org/10.1145/3610978.3640589

• G. Jäger, G. Licht, N. Seyffer, and S. Reitmann. 2024. VR-Based Teleoperation of Autonomous Vehicles for Operation Recovery. Ada Lett. 43, 2 (December 2023), 25–29. https://doi.org/10.1145/3672359.3672361

• S. Reitmann, B. Jung. Generating Synthetic Labeled Data of Animated Fish Swarms in 3D Worlds with Particle Systems and Virtual Sound Wave Sensors. In: Arseniev, D.G., Aouf, N. (eds) Cyber-Physical Systems and Control II. CPS&C 2021. Lecture Notes in Networks and Systems, vol 460. Springer, Cham. (Best Paper Award) URL: https://link.springer.com/chapter/10.1007/978-3-031-20875-1_12

• Florian Richter, Stefan Reitmann, and Bernhard Jung. “Integration of Open Geodata into Virtual Worlds”. In: the 6th International Conference on Virtual and Augmented Reality Simulations (ICVARS 2022), March 25–27, 2022, Brisbane, QLD, Australia. ACM, New York, NY, USA 5 Pages. URL: https://doi.org/10.1145/3546607.3546609

• S. Reitmann, E. V. Kudryashova, B. Jung und V. Reitmann. “Classification of Point Clouds with Neural Networks and Continuum-Type Memories”. In: Artificial Intelligence Applications and Innovations - AIAI 2021. IFIP Advances in Information and Communication Technology, Band 627, Springer, 2021, S. 505-517. ISBN: 978-3-030-79150-6 DOI: 10.1007/978-3-030-79150-6_40. URL: https://doi.org/10.1007/978-3-030-79150-6_40

• S. Reitmann und M. Schultz. “Computation of Air Traffic Flow Management Performance with Long Short-Term Memories Considering Weather Impact”. In: Artificial Neural Networks and Machine Learning – ICANN 2018. Bd. 11140. Lecture Notes in Computer Science. Springer, 2018, S. 532–541. ISBN: 978-3-030-01421-6. DOI: 10.1007/978-3-030-01421-6_51. URL: http://dx.doi.org/10.1007/978-3-030-01421-6_51.

• S. Reitmann und K. Nachtigall. “Applying Bidirectional Long Short-Term Memories (BLSTM) to Performance Data in Air Traffic Management for System Identification.” In: ICANN (2). Hrsg. von Alessandra Lintas u. a. Bd. 10614. Lecture Notes in Computer Science. Springer, 2017, S. 528–536. ISBN: 978-3-319-68612-7. URL: https://doi.org/10.1007/978-3-319-68612-7_60.

Theses:

• S. Reitmann. “Edge-AI-gestützte Erkennung von Schlafzuständen unter unsteten Umgebungsbedingungen mit ressourcenbeschränkter Hardware”. Master Thesis. FernUniversität Hagen. 2026

• S. Reitmann. “Künstliche neuronale Netze im leistungsbasierten Luftverkehrsmanagement”. PhD Thesis. TU Dresden, 2020. URL: https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-729299.

• S. Reitmann. “Entwicklung einer Methodik zur Erstellung generischer Flugpläne für Flughafencluster”. Diploma Thesis. TU Dresden. 2015.

• S. Reitmann. “Entwicklung eines Modells zum Vergleich von Flugprofilen unter Berücksichtigung stochastischer Störgrößen”. 2014.