Spin-glass theory and its applications to optimization problems, error-correcting codes, and signal processing
Deep learning (esp. deep unfolding)-based trainable iterative algorithms for wireless communications and signal processing
Typical performance of approximation algorithms for NP-hard problems
Phase transitions on complex networks, esp. random (geometric) graphs and ad-hoc wireless sensor networks