About
About Me
I am a researcher with a background in AI and Robotics, currently working on hardware-aware explainable reinforcement learning for cyber-physical systems. I completed my Master’s degree in Computer Engineering (AI & Robotics specialization) at the University of Padova and bring several years of prior industry experience as a software engineer.
My research focuses on hardrware aware RL environments, energy-efficient network control, and explainable AI (XAI) for real-world, safety-critical systems. I am closely associated with the CAUSE research training group, and my work bridges theory, system modeling, and deployable architectures.
I am open to collaboration on related research projects.
Current Research
- Reinforcement learning for cellular and network optimization
- Hardware-aware RL (power amplifier efficiency, power models, switching costs)
- Energy-efficient base station and cell-level control
- Explainable reinforcement learning (SHAP, LIME, custom explainability metrics)
- Measurement-based environments and concept drift awareness
Other Interests
- Multi-agent reinforcement learning and distributed control
- Graph Neural Networks for spatially coupled systems
- AI for communication networks
- Explainable AI for safety-critical and real-time systems
- Hardware-aware ML systems
- Reinforcement Lerarning for industrial robots.