The field of signal processing and network optimization is moving towards incorporating structured measurements and group equivariant techniques to improve recovery outcomes and reduce computational complexity. Recent work has focused on developing frameworks for sparse recovery from group orbits, leveraging symmetries in signal processing, and applying optimal transport methods to compute key performance indicators. Notable papers include: Sparse Recovery from Group Orbits, which establishes a comprehensive framework for sparse recovery of group-structured measurements. Reconstruction of Sparse Urban Wireless Signals via Group Equivariant Non-Expansive Operators, which introduces a novel approach for SINR map reconstruction in urban wireless communication networks using extremely sparse sampling.