Template User

University Assistant

+43 1 58801 18491

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Short CV

Murturi is a university assistant and PhD student at the Distributed Systems Group of the Institute of Information Systems Engineering. After receiving his bachelor’s degree in 2011, he started working as an intern in Robert Bosch GmbH, at the Division of Electrical Vehicles and Hybrid Systems, Germany. In 2015, he received his master’s degree in Computer Engineering at the University of Prishtina where he continued his career as a university assistant. In 2018, he joined the Distributed Systems Group.

Research Interests



Thesis & Project Supervision

If you are interested in a topic that fits my research interests, I can (co-)advise your master theses. Furthermore, I can offer that we elaborate a topic together, based on your specific interests.

Co-Supervised Theses


  1. Murturi, I., Jia, C., Kerbl, B., Wimmer, M., Dustdar, S., & Tsigkanos, C. (2021). On Provisioning Procedural Geometry Workloads on Edge Architectures. In 17th International Conference on Web Information Systems and Technologies (WEBIST) (pp. 1–6). Accepted.
  2. Murturi, I., Egyed, A., & Dustdar, S. (2021). Utilizing AI Planning on the Edge. In IEEE Internet Computing. (to appear).
  3. Murturi, I., & Dustdar, S. (2021). A Decentralized Approach for Resource Discovery using Metadata Replication in Edge Networks. IEEE Transactions on Services Computing.
  4. Dustdar, S., & Murturi, I. (2021). Towards IoT Processes on the Edge. In Next-Gen Digital Services. A Retrospective and Roadmap for Service Computing of the Future (pp. 167–178). Springer.
  5. Murturi, I. (2021). Transforming the Method of Least Squares to the Dataflow Paradigm. In Handbook of Research on Methodologies and Applications of Supercomputing (pp. 114–121). IGI Global.
  6. Dustdar, S., & Murturi, I. (2020). Towards Distributed Edge-based Systems. In 2020 IEEE Second International Conference on Cognitive Machine Intelligence (CogMI) (pp. 1–9). IEEE.
  7. Murturi, I., Barzegaran, M., & Dustdar, S. (2020). A Decentralized Approach for Determining Configurator Placement in Dynamic Edge Networks. In IEEE 2nd International Conference on Cognitive Machine Intelligence (CogMI 2020) (pp. 1–10). IEEE.
  8. Dustdar, S., & Murturi, I. (2020). Towards Distributed Edge-based Systems. In IEEE 2nd International Conference on Cognitive Machine Intelligence (CogMI 2020) (pp. 1–9). IEEE.
  9. Alkhabbas, F., Murturi, I., Spalazzese, R., Davidsson, P., & Dustdar, S. (2020). A Goal-driven Approach for Deploying Self-adaptive IoT Systems. In IEEE International Conference on Software Architecture (ICSA 2020) (pp. 1–11). IEEE.
  10. Avasalcai, C., Murturi, I., & Dustdar, S. (2020). Edge and Fog: A Survey, Use Cases, and Future Challenges. Fog Computing: Theory and Practice.
  11. Arleo, A., Tsigkanos, C., Jia, C., Leite, R. A., Murturi, I., Klaffenboeck, M., … Sorger, J. (2019). Sabrina: Modeling and Visualization of Economy Data with Incremental Domain Knowledge. ArXiv Preprint ArXiv:1908.07479.
  12. Murturi, I., Avasalcai, C., Tsigkanos, C., & Dustdar, S. (2019). Edge-to-Edge Resource Discovery using Metadata Replication. In 2019 IEEE 3rd International Conference on Fog and Edge Computing (ICFEC) (pp. 1–6). IEEE.
  13. Tsigkanos, C., Murturi, I., & Dustdar, S. (2019). Dependable Resource Coordination on the Edge at Runtime. In Proceedings of the IEEE, 2019 (pp. 1–17).
  14. Dustdar, S., Avasalcai, C., & Murturi, I. (2019). Edge and Fog Computing: Vision and Research Challenges. In 2019 IEEE International Conference on Service-Oriented System Engineering (SOSE) (pp. 96–9609). IEEE.
  15. Rexha, B., & Murturi, I. (2019). Applying efficient crowdsourcing techniques for increasing quality and transparency of election processes. Electronic Government, an International Journal, 15(1), 107–128.
  16. Bajrami, X., & Murturi, I. (2018). An efficient approach to monitoring environmental conditions using a wireless sensor network and NodeMCU. Elektrotechnik Und Informationstechnik, 135(3), 294–301.

Academic Activities

I have been an official reviewer for: