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Jasmin Jahić

Bachelor – Technical Computer science; Master – Robotics; PhD – Electrical and Computer Engineering

Director of Studies in Computer Science, Queens’ College and Visiting Researcher, Department of Computer Science, University of Cambridge

About me

Jasmin’s research focuses on concurrent software systems and software system architectures. He actively contributes to EU research committee for creating Electronic Components and Systems Strategic Research and Innovation Agenda (https://ecssria.eu/(Opens in a new window)) as a manager leading a team of 25 experts. He has also served on program committees for various high-profile conferences.

Jasmin holds a MSc degree in Robotics from Ecole Centrale de Nantes, France. At the University of Kaiserslautern, Germany he obtained his PhD in Electrical and Computer Engineering in 2020, focusing on testing concurrent software systems. From January 2013 to June 2019, he worked as a project manager and a researcher at Fraunhofer Institute for Experimental Software Engineering (IESE) in Germany, mainly focusing on software system architectures for embedded systems. Besides working as a researcher and manager in public and industry projects in the areas of embedded software architecture, modelling, and simulation, during his time at IESE, he was in the core team of two fully funded EU level project proposals — ECSEL and H2020 funding schemes.



  • Matar, R. & Jahić, J. (2023). An approach for evaluating the potential impact of anti-patterns on microservices performance, 2023 IEEE 20th International Conference on Software Architecture Companion, 167–170. https://doi.org/10.1109/ICSA-C57050.2023.00044

  • Helwani, F.& Jahić, J. (2022). ACIA: A methodology for identification of architectural design patterns that support continuous integration based on continuous assessment, 2022 IEEE 19th International Conference on Software Architecture, 198–205.https://doi.org/10.1109/ICSA-C54293.2022.00046

  • Jahic, J.,Roitsch, R. & Grzymkowski, L. (2021). Knowledge-based adequacy assessment approach to support AI adoption,2021 IEEE International Conference on Software ArchitectureCompanion, 8–14. https://doi.org/10.1109/ICSA-C52384.2021.00008

  • Jahić, J., Bauer, T., Kuhn, T., Wehn, N. & Antonino, P.O. (2020). FERA: A framework for critical assessment of execution monitoring based approaches for finding concurrency bugs. In K. Arai, S. Kapoor, and R. Bhatia, eds.,Intelligent Computing: Proceedings of the 2020 SAI computing conference, 1. also in Advances in Intelligent Systems and Computing, 1228. https://doi.org/10.1007/978-3-030-52249-0_5

  • Jahić, J. & Roitsch, R. (2020). State of the practice survey: predicting the influence of AI adoption on system software architecture in traditional embedded systems. In H. Muccini, et al., Software Architecture (proceedings of the 14th European conference, ECSA 2020 tracks and workshops), also inCommunications in Computer and Information Science, 1269. https://doi.org/10.1007/978-3-030-59155-7_12(Opens in a new window)

  • Jahić, J.,Enbrecht, P., Mayer, U. & Antonino, P. O. (2019). Mitigating the influence of embedded software development environments and toolsets (ESDT) on software architecture. 2019 IEEE International Conference on Software Architecture, 111–120. https://doi.org/10.1109/ICSA.2019.00020.