The REAL Lab conducts research at the intersection of learning, decision-making, and communication systems, with the overarching goal of enabling intelligent, scalable, and adaptive future networks.
Our work combines theoretical foundations, algorithm design, and experimental validation to develop learning-driven solutions that optimize how information is generated, transmitted, and utilized in complex networked environments.
Bridging the gap between simulation and reality using Reinforcement Learning.
A-403, Dept of EEE, METU
Ankara, Turkiye