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 focuses on developing robust, interpretable models for intelligent network management, with an emphasis on real‑world reliability and generalization.

Current focus. My current research leverages Large Language Models (LLMs) for trustworthy autonomous networks, with emphasis on reliability under distribution shift, interpretable and auditable decision processes across operational 5G/6G environments.

Background. Previously, As an AI Researcher, I worked on Edge AI at STMicroelectronics, designing quantization‑aware, memory‑efficient neural networks implemented on Intelligent Sensor Processing Units (ISPU). I hold an M.Sc. in Telecommunication Engineering (specialization in signals & data analysis) from Politecnico di Milano.

Research Interests
Trustworthy / Explainable AI (XAI) LLMs for Network Automation Domain Adaptation & Generalization Representation Learning Robust AI/ML for Communication Systems Edge AI
News & Updates
Feb 2025
Doctoral Research: I started my PhD at Chalmers University of Technology.
Jan 2025
Role Transition: After delivering an MVP integrating LLM capabilities into the platform, I moved on to begin my PhD journey.
Oct 2024
New Role: I joined AGap2 as a Generative AI Engineer to contribute to the AI Factory lab's digital reporting project for Rina.
Oct 2024
New Publication: Our paper "Inertial Measurement Unit Self-Calibration by Quantization-Aware and Memory-Parsimonious Neural Networks" has been accepted in the Electronics journal.
Jul 2024
New Publication: Our paper, "IMU User-Transparent Tiny Neural Self-Calibration", has been accepted for presentation at the IEEE RTSI Conference.
Jul 2024
Master's Thesis Defense: Successfully defended with full marks my Master's thesis titled "Continuous IMU-MEMS Self-Calibration Process by Means of Tiny Neural Networks" at Politecnico di Milano.
Nov 2023
Master's Thesis: I joined the AI Software and Tools – System Research and Applications team at STMicroelectronics as an AI researcher to conduct my master’s thesis on edge AI.

Publications
Journal Articles
  1. 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
Conference Papers
  1. 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
  2. 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.
Theses
  1. 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
Portrait of Kiarash Rezaei

Kiarash Rezaei

Ph.D. Student
Chalmers University of Technology
Communication, Antennas & Optical Networks

kiarashr@chalmers.se
Gothenburg, Sweden

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