Workshop — Geometric Inequalities, Convexity and Probability

Mathematical developments of the last decades indicate that geometry of high dimensions, when viewed correctly, creates remarkable order and simplicity rather than untamed complexity. Its applications permeated the fields of analysis and probability, reaching far away domains as Theoretical Computer Science and Statistical Physics while, simultaneously, methods and techniques came from a variety of directions ranging from classical analysis and probability to dynamical systems and topological methods. Recent striking results such as the near resolution of the Kannan, Lov\'asz and Simonovits (KLS) conjecture and the Bourgain slicing problem, the proof of the Gaussian Correlation Conjecture and advances in concentration of measure, make ripe the timing of this workshop on the effects of convexity and probability on high-dimensional geometric phenomena. By exploiting the scientific momentum, the workshop aims to engage a new generation in exciting collaborations and research directions.