Foundations
The research behind the practical work — multi-agent reinforcement learning, federated systems, and AI for next-generation networks.
My research applies machine learning and AI to complex problems in 6G networks and smart systems, at the intersection of telecommunications, deep learning and optimization theory.
That background is what I lean on when a business problem genuinely needs a model — forecasting, anomaly detection, distributed learning — and, just as usefully, when it doesn't.
Expertise
AI-powered solutions for next-gen wireless networks
Leveraging ML and AI to create efficient, secure, and adaptive communication systems.
Featured Publication
COMIX: Generalized Conflict Management in O-RAN xApps
Cooperative and distributed learning approaches
Developing algorithms for multiple AI agents to learn and work together effectively.
Featured Project
Multi-Agent Energy Management System
Intelligent infrastructure and resource optimization
Integrating AI and ML into IoT devices and infrastructure for responsive environments.
Open to research collaborations — and to putting any of this to work on a production problem.
