I’m a PhD researcher at Chalmers University of Technology, working at the intersection of trustworthy AI, explainable machine learning, and communication systems. My research focuses on building robust, interpretable models for intelligent network management, with an emphasis on real-world reliability and generalization.
Before joining Chalmers, I worked as an AI Researcher at STMicroelectronics and in different machine learning and data science roles at the startups Datalobster and Envision and at RINA, focusing on reliable ML for safety-critical systems.
I hold an MSc in Telecommunication Engineering from Politecnico di Milano, where I specialized in signal processing, statistical learning, and AI foundations.
- Trustworthy AI and Uncertainty Quantification
- Domain Adaptation, Generalization and Representation Learning
- Reliable ML for Communication & Networked Systems
- Edge AI
- I’m always open to research collaborations, technical discussions, and academic exchange in these areas.
📫 Connect with me on LinkedIn or reach out via email
- ⚡ Fun fact: I’m passionate about bridging the gap between black-box models and human understanding.
- accepted for oral presentation at OFC 2026
2- Generative Explainability for Next-Generation Networks: LLM-Augmented XAI with Mutual Feature Interactions
- Presented at GenXNet Workshop, IEEE WiMob 2025 conference
- Published in Electronics Journal, October 2024
- Presented at IEEE RTSI 2024
- Built a real-time vehicle detection and counting system using YOLOv8 and BYTETrack.
- Focused on smart transportation systems and high-density environments.
- Developed ML models to detect signal anomalies in optical transponders using constellation diagrams.
- Conducted a comparative study on classifiers for biomedical image analysis using XAI techniques like GradCAM and SHAP.
- Analyzed KPIs for 20 companies to optimize e-marketing strategies, a project proposed by Google Italy.
Politecnico di Milano
- Specialization: Signals and Data Analysis
- Thesis: Continuous IMU-MEMS Self-Calibration Process by Means of Tiny Neural Networks
Kharazmi University of Tehran
- Thesis: Automatic Architecture Design of CNNs using Genetic Algorithm and Reinforcement Learning (MetaQNN)
- IEEE student member
- Member of PoliMi Data Science Association.
- Executive Staff at CICIS 2019 national conference.