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
Dr Jahić is a Director of Studies in Computer Science at Queens’ College at the University of Cambridge. He also works as a researcher at the Department of Computer Science (University of Cambridge), specialising in software systems architectures, application of artificial intelligence in software engineering, and concurrent software systems. He is a guest lecturer at the University of Kaiserslautern-Landau (Germany), where he leads a course on software architecture in embedded systems with the focus on automotive systems.
He completed his PhD at the University of Kaiserslautern, Germany and worked as a researcher and project manager at Fraunhofer Institute for Experimental Software Engineering.
He has extensive experience in EU-level projects and industry collaborations. Dr Jahić has contributed to numerous high-profile conferences and academic publications on software architecture.
He serves as a reviewer for International Conference for Software Architecture (ICSA) and Journal of Systems and Software, both premium venues for publishing research in software architecture.
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The impact of AI-Generated solutions on software architecture and productivity: Results from a survey study (opens in a new tab), Amasanti, G. & Jahić, J. (2025).European Conference on Software Architecture (ECSA 2025).
State of practice: LLMs in software engineering and software architecture (opens in a new tab), Jahić, J. & Sami, A. (2024). IEEE 21st International Conference on Software Architecture Companion (ICSA-C), 311–318.
An approach for evaluating the potential impact of anti-patterns on microservices performance (opens in a new tab), Matar, R. & Jahić, J. (2023). IEEE 20th International Conference on Software Architecture Companion, 167–170.
ACIA: A methodology for identification of architectural design patterns that support continuous integration based on continuous assessment (opens in a new tab), Helwani, F. & Jahić, J. (2022). IEEE 19th International Conference on Software Architecture, 198–205.
Knowledge-based adequacy assessment approach to support AI adoption (opens in a new tab), Jahić, J. et.al. (2021). IEEE 18th International Conference on Software Architecture Companion, 8–14.
FERA: A framework for critical assessment of execution monitoring based approaches for finding concurrency bugs (opens in a new tab), Jahić, J. et.al. (2020). Intelligent Computing. SAI 2020. Advances in Intelligent Systems and Computing, vol 1228, 54–74.
State of the practice survey: predicting the influence of AI adoption on system software architecture in traditional embedded systems (opens in a new tab), Jahić, J. & Roitsch, R. (2020). Software Architecture. ECSA 2020. Communications in Computer and Information Science, vol 1269, 155–169.
Mitigating the influence of embedded software development environments and toolsets (ESDT) on software architecture (opens in a new tab), Jahić, J. et. al. (2019). IEEE International Conference on Software Architecture, 111–120.
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