I’m a first-year Ph.D. student at Chalmers University of Technology, working at the intersection of Trustworthy AI, Explainable Machine Learning, and Communication Systems. My research is driven by a central goal: enabling AI-powered network management that remains reliable, interpretable, and robust in real-world 5G/6G deployments.
Current focus. I investigate uncertainty quantification as a foundation for trustworthy autonomous networks. Specifically, I study how learning-based systems can recognise when their predictions may be unreliable, respond to distribution shifts, and communicate uncertainty in ways that support transparent and auditable decision-making in operational networks.
Background. I received my M.Sc. in Telecommunication Engineering, specializing in Signals and Data Analysis, from Politecnico di Milano. My master’s research at STMicroelectronics focused on developing quantization-aware, memory-efficient neural networks for sensor self-calibration on resource-constrained Intelligent Sensor Processing Units (ISPUs). Before joining Chalmers, I held industry positions as an AI Researcher and Data Scientist, developing machine learning systems ranging from resource-constrained Edge AI to generative AI solutions for industrial applications.
- Cardoni, M., Pau, D. P., Rezaei, K., & Mura, C. (2024). Inertial Measurement Unit Self-Calibration by Quantization-Aware and Memory-Parsimonious Neural Networks. Electronics, 13(21). https://doi.org/10.3390/electronics13214278
- Rezaei, K., Ayoub, O., Monti, P., & Natalino, C. (2026). Human-Grounded Evaluation of Large Language Models for Optical Network Automation. 2026 International Conference on Transparent Optical Networks (ICTON).
- Rezaei, K., Ayoub, O., Natalino, C., & Monti, P. (2026). Bridging the Trust Gap in AI-Driven Optical Networks with Structured Explainability. 2026 Opto-Electronics and Communications Conference (OECC).
- Rezaei, K., Omran, A., Monti, P., & Natalino, C. (2026). Policy-driven Conformal Prediction for Trustworthy QoT Estimation. 2026 Optical Fiber Communication Conference (OFC). https://research.chalmers.se/publication/549958/file/549958_Fulltext.pdf
- Rezaei, K., Omran, A., Troia, S., Lelli, F., Monti, P., & Natalino, C. (2025). Generative Explainability for Next-Generation Networks: Llm-Augmented Xai with Mutual Feature Interactions. 2025 21th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 1–6. https://doi.org/10.1109/WiMob66857.2025.11257542
- Cardoni, M., Pau, D. P., & Rezaei, K. (2024). IMU User Transparent Tiny Neural Self-Calibration. 2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI), 619–624. https://doi.org/10.1109/RTSI61910.2024.10761916
- Rezaei, K., & Zamani, S. (2019). An Introduction to Convolutional Neural Networks and Applications. 2019 4th National Conference on Contemporary Issues in Computer and Information Sciences (CICIS), 561–569.
- Rezaei, K. (2023). Continuous IMU-MEMS Self-Calibration Process by Means of Tiny Neural Networks [Master’s thesis, Politecnico di Milano]. https://hdl.handle.net/10589/221852
Kiarash Rezaei
Ph.D. Student
Chalmers University of Technology
Communication, Antennas & Optical Networks
kiarashr@chalmers.se
Gothenburg, Sweden