Currently, LICAN focuses on a number of interdisciplinary topics in wireless communications, wireless networking, and machine learning. In particular, the group works on theoretical models and algorithms for reinforcement learning, multi-armed bandits, and their practical engineering applications in spectrum access, signal classification, wireless network management, edge intelligence, and federated learning. The group is also interested in machine learning and statistics for medicine, in particular clinical trials and heterogeneous treatment effects.
LICAN’s research pushes the frontier of both communication and networking systems and machine learning on the edge. We explore novel tools, develop advanced algorithms and identify potential engineering applications. Our research spans from theoretical models, algorithm designs to system simulations, lab testbeds and real-world use cases.