Current wireless networks are reaching a level of complexity in which conventional models and design tools are no longer valid, and fail to provide the ever-growing performance requirements in terms of peak rates and mobility that users demand nowadays. Delay constraints, scaling laws, parameter estimation (e.g., in massive MIMO networks), interference management and modeling techniques, and distributed implementations are some of the challenging aspects to be researched for next-generation wireless networks. This calls for creative cross-disciplinary methods to analyze, model, understand, and design algorithms for future wireless networks, which will be characterized by denser and heterogeneous deployments. Recently, there have been several fruitful insights and approaches inspired from the areas of physics and mathematics, including statistical mechanics, elementary particle physics, algebraic and stochastic geometry, machine learning, electrostatics, game theory, and random matrix theory, among others. This interdisciplinary workshop aims to bring together active researchers with different backgrounds interested in research on future wireless communications and networks.