Konstantin Dmitriev, M.Sc.

Konstantin Dmitriev, M.Sc.

Institute of Flight System Dynamics
Technische Universität München
Boltzmannstr. 15
85748 Garching bei München
Germany
Room:MW3601 (floor plan)
Phone:+49 89 289 16570
Fax:+49 89 289 16058
E-mail:konstantin.dmitriev@tum.de

Publications

K. Dmitriev, J. Rhein, L. Beller, J. Bröcker, E. Huber, J. Schumann, F. Holzapfel, "Safety Assessment of a Machine Learning-Based Aircraft Emergency Braking System: A Case Study", in 2024 IEEE/AIAA 43rd Digital Avionics Systems Conference (DASC), IEEE. [doi]
P. Panchal, K. Dmitriev, S. Myschik, F. Holzapfel, "Comprehensive Overview of a Process-Oriented Build Tool for Airborne Safety-Critical Software Development", in 2023 10th International Conference on Recent Advances in Air and Space Technologies (RAST), IEEE. [doi]
K. Dmitriev, F. Kaakai, M. Ibrahim, U. Durak, B. Potter, F. Holzapfel, "Tool Qualification Aspects in ML-Based Airborne Systems Development", in Software Engineering 2023 Workshops, Groher, Iris, Vogel, Thomas, Eds., Bonn: Gesellschaft für Informatik e.V.. [doi]
K. Dmitriev, J. Schumann, I. Bostanov, M. Abdelhamid, F. Holzapfel, "Runway Sign Classifier: A DAL C Certifiable Machine Learning System", in 2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC), IEEE. [doi]
P. Panchal, S. Myschik, K. Dmitriev, F. Holzapfel, "Application of a Process-Oriented Build Tool to an INDI-Based Flight Control Algorithm", in AIAA AVIATION 2022 Forum. [doi]
P. Panchal, N. Sorokina, S. Myschik, K. Dmitriev, F. Holzapfel, "Application of a Process-Oriented Build Tool to the Development of a BM3 Slave Controller Software Module", in Deutscher Luft- und Raumfahrtkongress 2022, Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V.. [doi]
P. Panchal, S. Myschik, K. Dmitriev, P. Bhardwaj, F. Holzapfel, "Handling Complex System Architectures with a DO-178C/DO-331 Process-Oriented Build Tool", in 2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC). [doi]
F. Kaakai, K. Dmitriev, E. Baskaya, E. Bezzecchi, R. Bharadwaj, B. Brown, G. Gentile, C. Gingins, S. Grihon, C. Travers, "Toward a Machine Learning Development Lifecycle for Product Certification and Approval in Aviation", SAE International Journal of Aerospace, vol. 15, no. 2, 2022, pp. 127-143. [doi]
K. Dmitriev, J. Schumann and F. Holzapfel, "Towards Design Assurance Level C for Machine-Learning Airborne Applications", in 2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC). [doi]
K. Dmitriev, J. Schumann and F. Holzapfel, "Toward Design Assurance of Machine-Learning Airborne Systems", in AIAA SciTech 2022 Forum. [doi]
K. Schmiechen, S. A. Zafar, K. Dmitriev, C. Krammer, M. Maly, F. Holzapfel, "A Requirements Management Template in Polarion for Model-Based Development of Airborne Systems", in Proceedings of the Software Engineering 2021 Satellite Events.
K. Dmitriev, J. Schumann and F. Holzapfel, "Toward Certification of Machine-Learning Systems for Low Criticality Airborne Applications", in 2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC). [doi]
K. Dmitriev, S. A. Zafar, K. Schmiechen, Y. Lai, M. Saleab, P. Nagarajan, D. Dollinger, M. Hochstrasser, F. Holzapfel, S. Myschik, "Lean and Highly-automated Model-Based Software Development Process", in 2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC). [doi]

Supervised Student Theses

A. Keshavarzmohammadian, "Development of dataset and ML models for aerial images semantic segmentation", Thesis, Technische Universität München, Garching, 2026.
J. Rudrapatnam Kumar, "Certification Aspects of an AI Based Image Navigation System for an UAS", Thesis, Technische Universität München, Garching, 2024.
C. M. Capdevila Llompart, "Towards a Regulatory Framework for the Certification of AI/ML-based Airborne Systems in Military Aviation", Thesis, Technische Universität München, Garching, 2023.
I. Bostanov, "Development and Integration of a Deep Neural Network for a Certifiable Airborne System", Thesis, Technische Universität München, Garching, 2023.
M. Abdelhamid, "Development of Traceability Connector Tool for Linking Polarion Requirements with Machine Learning Datasets", Thesis, Technische Universität München, Garching, 2023.