The IAS Frontiers Conference on Geometry, Dynamics, and Learning will bring together an international cohort of leading researchers, early-career investigators, and promising graduate students working at the interface of geometric analysis, dynamical systems, and machine learning. Over the past decade, a convergence of ideas from pure mathematics, data science, and theoretical computer science has catalysed a new research frontier in which tools from differential geometry and dynamical systems theory inform the design, analysis, and interpretability of modern learning algorithms, and, conversely, insights from learning are reshaping foundational questions in geometry and dynamics.
The primary goals of this workshop are to (1) cultivate new intellectual bridges between geometry, dynamical systems, and learning theory; (2) identify shared research challenges and unify disparate methodological frameworks; and (3) accelerate collaborative projects that leverage mathematical rigor to address practical problems in data-driven science and engineering.
