E. Kusmenko

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

room 4220

Field of Work

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


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