Dr. rer. nat. Evgeny Kusmenko Software Engineering Department of Computer Science 3 RWTH Aachen University Ahornstraße 55 D-52074 Aachen tel. +49 (241) 80-21342 kusmenkose-rwth.de room 4220

Field of Work

• Automotive
• Autonomous Vehicles
• Machine Learning and Data Science
• Robotics
• Software Architectures

Publications

• [Kus21] E. Kusmenko:
  Model-Driven Development Methodology and Domain-Specific Languages for the Design of Artificial Intelligence in Cyber-Physical Systems.
  In: Aachener Informatik-Berichte, Software Engineering, Band 49, ISBN 978-3-8440-8286-9. Shaker Verlag, November 2021.
• [HKR21a] M. Heithoff, E. Kusmenko, B. Rumpe:
  Synchronous Execution Semantics for Component & Connector Models.
  In: S. Bin Abid, R. Oliveira, I. Ober, editors, Companion Proceedings of MODELS 2021. Workshop MoDeVVa, 264-273, ACM/IEEE, Oct. 2021.
• [AKK+21] A. Atouani, J. C. Kirchhof, E. Kusmenko, B. Rumpe:
  Artifact and Reference Models for Generative Machine Learning Frameworks and Build Systems.
  In: E. Tilevich, C. De Roover, editors, Proceedings of the 20th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences (GPCE ’21), Volume 20, ACM SIGPLAN, Oct. 2021.
• [KPRS19] E. Kusmenko, S. Pavlitskaya, B. Rumpe, S. Stüber:
  On the Engineering of AI-Driven Systems.
  In: ASE’19. Software Engineering Intelligence Workshop (SEI’19), pp. 126-133, San Diego, Nov. 2019.
• [KNP+19] E. Kusmenko, S. Nickels, S. Pavlitskaya, B. Rumpe, T. Timmermanns:
  Modeling and Training of Neural Processing Architectures.
  In: Conference on Model Driven Engineering Languages and Systems (MODELS'19), pp. 283-293, IEEE, Munich, Sep. 2019.
• [GKR19] N. Gatto, E. Kusmenko, B. Rumpe:
  Modeling Deep Reinforcement Learning Based Architectures for Cyber-Physical Systems.
  In: Proceedings of MODELS 2019. Workshop MDE Intelligence, pp. 196-202, IEEE, Munich, Sep. 2019.
• [KKRZ19] J. C. Kirchhof, E. Kusmenko, B. Rumpe, H. Zhang:
  Simulation as a Service for Cooperative Vehicles.
  In: Proceedings of MODELS 2019. Workshop MASE, pp. 28-37, IEEE, Munich, Sep. 2019.
• [KKMR19] J. C. Kirchhof, E. Kusmenko, J. Meurice, B. Rumpe:
  Simulation of Model Execution for Embedded Systems.
  In: Proceedings of MODELS 2019. Workshop MLE, pp. 331-338, IEEE, Munich, Sep. 2019.
• [KKR19] N. Kaminski, E. Kusmenko, B. Rumpe:
  Modeling Dynamic Architectures of Self-Adaptive Cooperative Systems.
  In: The Journal of Object Technology, 18(2), pp. 1-20. July 2019.
• [HKKR19] A. Hellwig, S. Kriebel, E. Kusmenko, B. Rumpe:
  Component-based Integration of Interconnected Vehicle Architectures.
  In: 30th Intelligent Vehicles Symposium (IV'19). Workshop on Cooperative Interactive Vehicles, pp. 146-151, IEEE, Paris, June 2019.
• [KKRS19] S. Kriebel, E. Kusmenko, B. Rumpe, I. Shumeiko:
  Learning Error Patterns from Diagnosis Trouble Codes.
  In: 30th Intelligent Vehicles Symposium (IV'19). Workshop on Unsupervised Learning for Automated Driving, pp. 246-251, IEEE, Paris, June 2019.
• [DGH+19] I. Drave, T. Greifenberg, S. Hillemacher, S. Kriebel, E. Kusmenko, M. Markthaler, P. Orth, K. S. Salman, J. Richenhagen, B. Rumpe, C. Schulze, M. von Wenckstern, A. Wortmann:
  SMArDT modeling for automotive software testing.
  In: Software: Practice and Experience, 49(2):301-328, Feb. 2019.
• [BKL+18] C. Brecher, E. Kusmenko, A. Lindt, B. Rumpe, S. Storms, S. Wein, M. von Wenckstern, A. Wortmann:
  Multi-Level Modeling Framework for Machine as a Service Applications Based on Product Process Resource Models.
  International Symposium on Computer Science and Intelligent Control (ISCSIC'18). Stockholm, ACM, Sep. 2018.
• [FIK+18] C. Frohn, P. Ilov, S. Kriebel, E. Kusmenko, B. Rumpe, A. Ryndin:
  Distributed Simulation of Cooperatively Interacting Vehicles.
  In: International Conference on Intelligent Transportation Systems (ITSC'18), pg. 596-601, IEEE, 2018.
• [KRSvW18a] E. Kusmenko, B. Rumpe, S. Schneiders, M. von Wenckstern:
  Highly-Optimizing and Multi-Target Compiler for Embedded System Models: C++ Compiler Toolchain for the Component and Connector Language EmbeddedMontiArc.
  In: Conference on Model Driven Engineering Languages and Systems (MODELS'18), pg. 447-457, Copenhagen, ACM, Oct. 2018.
  
  • Additional Materials.
• [KRSvW18] E. Kusmenko, B. Rumpe, I. Strepkov, M. von Wenckstern:
  Teaching Playground for C&C Language EmbeddedMontiArc.
  In: Proceedings of MODELS 2018. Workshop ModComp, Copenhagen, Oct. 2018.
• [KRRvW18] E. Kusmenko, J. Ronck, B. Rumpe, M. von Wenckstern:
  EmbeddedMontiArc: Textual Modeling Alternative to Simulink.
  In: Proceedings of MODELS 2018. Workshop EXE, Copenhagen, Oct. 2018.
• [KKRW18] S. Kriebel, E. Kusmenko, B. Rumpe, M. von Wenckstern:
  Finding Inconsistencies in Design Models and Requirements by Applying the SMARDT Process.
  In: Modellbasierte Entwicklung eingebetteter Systeme (MBEES’18)
• [KSRW18] E. Kusmenko, I. Shumeiko, B. Rumpe, M. von Wenckstern:
  Fast Simulation Preorder Algorithm.
  In: Proceedings of the 6th International Conference on Model-Driven Engineering and Software Development (MODELSWARD'18), pg. 256-267. SciTePress, Jan. 2018.
• [HKK+18] S. Hillemacher, S. Kriebel, E. Kusmenko, M. Lorang, B. Rumpe, A. Sema, G. Strobl, M. von Wenckstern:
  Model-Based Development of Self-Adaptive Autonomous Vehicles using the SMARDT Methodology.
  In: Proceedings of the 6th International Conference on Model-Driven Engineering and Software Development (MODELSWARD'18), pg. 163-178. SciTePress, Jan. 2018.
• [GKR+17] F. Grazioli, E. Kusmenko, A. Roth, B. Rumpe, M. von Wenckstern:
  Simulation Framework for Executing Component and Connector Models of Self-Driving Vehicles.
  In: Proceedings of MODELS 2017 Satellite Event. Workshop EXE, Austin, Texas, CEUR Workshop Proceedings, Sept. 2017.
• [KRRW17] E. Kusmenko, A. Roth, B. Rumpe, M. von Wenckstern:
  Modeling Architectures of Cyber Physical Systems.
  In: European Conference on Modelling Foundations and Applications (ECMFA'17), Marburg, pg. 34-50. LNCS 10376, Springer, July 2017.
• [DDE+17] J. Dankert, C. Dernehl, L. Eckstein, S. Kowalewski, E. Kusmenko, B. Rumpe, :
  RapidCoop - Robuste Architektur durch geeignete Paradigmen für Kooperativ Interagierende Automobile.
  In: Automatisiertes und Vernetztes Fahren (AAET'17), Braunschweig, Feb. 2017.

Supervised Bachelor/Master Thesis

• Fuß, Christian: Modellbasierte Image Caption Generation unter Anwendung von Attention-Mechanismen in EmbeddedMontiArcDL (MA), 2019
• Gatto, Nicola: Modeling and Training of Deep Reinforcement Learning based Architectures for Cyber-Physical Systems (MA), 2019
• Haala, Henk: Consistency Checks of Component and Connector Reconfigurations based on EmbeddedMontiArc Dynamics (BA), 2019
• Harputlu, Eyüp: Modellierung und Generierung des Trainings von tiefen neuronalen Netzwerkarchitekturen (BA), 2019
• Trotta, Danilo: Visualisierungs-Aspekte einer autonomen Fahrzeug-Simulation (BA), 2019
• Cam, Ebru: 3D-Visualisierung von Fahrzeugsimulation auf Basis von OpenStreetMap (BA), 2019
• Porta, Pascal Maurice: A Modeling Framework for the Continuous Simulation of Self-Driving Vehicles (BA), 2019
• Kaminski, Nils: Dynamische Verhaltensaktivierung in Komponenten- und Konnektor-Modellen (MA), 2019
• An Application Layer Protocol for Cooperative Driving (MA), 2019
• Zhang, Hengwen: A Distributed Simulator Architecture based on MontiSim (BA), 2019
• Bauer, Markus: Modeling Controllers for Cooperatively Interacting Vehicles (BA), 2019
• Meurice, Jean: Simulation of Hardware and Controller Execution in Au-tomotive Systems (BA), 2019
• Yeverino Rodriguez, Carlos Alfredo: Multi-Target Code Generation and Training of Deep Learning Networks for Autonomous Driving (MA), 2019
• Mönckemeyer, Felix: Model-based development of a distributed trajectory planning system for autonomous vehicles (BA), 2018
• Rexhepi, Bardh: Time Series Analysis and Prediction for Automotive Diagnosis (MA), 2018
• Jansen, Marvin: A Product Line for Simulator-Coupling in MontiSim (BA), 2018
• von Oy, Christoph: Modeling and Co-Simulation of Physical Vehicle Behavior (BA), 2018
• Pavlitskaya, Svetlana: Integration of Deep Learning Components into Autonomous Driving Architectures (MA), 2018
• Richter, Christoph: Model-predictive Trajectory Control and Simulation for Self-driving Vehicles (MA), 2018
• Timmermanns, Thomas: Modelling Languages for Deep Learning based Cyber-Physical Systems (MA), 2018
• Hellwig, Alexander: Modeling and Simulation of Cooperative Vehicles with MontiCAR and the ROS Simulation Framework (BA), 2018
• Napiorkowski, Sebastian: Leveraging Process Mining for Error Sequence Detection (MA), 2018
• Schmidt, Deniz: Model driven development of configurable vehicle simulations (BA), 2018
• Ilov, Petyo: Software architecture of distributed multi-user simulation of autonomously driving vehicles (MA), 2018
• Ryndin, Alexander: Modelling of Component-and-Connector Architectures for Autonomous Vehicles (MA), 2018
• Dao, Hoai: Similarity Measures for Categorical and Mixed Data (MA), 2018
• Schultz, Martin: Modelling dynamic Architectures for cooperative Vehicles (MA), 2018
• Martini, Melanie: Comparison of visualization techniques for high dimensional data (BA), 2018
• Dalgic, Baran: C&C Modellierung autonomen Fahrverhaltens und Simulation in Gazebo (BA), 2017
• Atouani, Abdallah: ROS basierte Simulation von C2C Kommunikation (BA), 2017
• Görick, Philipp: Matrix Properties in Type Systems of Component and Connector Based Languages (BA), 2017
• Schnackenberg, Alexander: Event-based Dynamic Reconfiguration of Component and Connector Architectures (BA), 2017
• Tabone, Luca: Architectures for Data Science Automation (MA), 2017
• Lorang, Mike: Model-based design and simulation of autonomous vehicle controllers (BA), 2017
• Scheidt, Leon: Qualitätsmaße für Clustering-Performance-Evaluation (BA), 2017
• Frohn, Christian: Simulation and Modeling of Vehicle-to-Vehicle Communication for Autonomously Driving Vehicles (MA), 2017
• Sema, Albi: Software Architectures for Deep Learning based Autonomous Driving (MA), 2017