In recent years, semidefinite programming has established itself as the central tool in convex nonlinear optimization. Compared to linear programming, it provides superior modeling power while still being computationally tractable. It has found many applications in various fields including control theory, combinatorial optimization, theoretical computer science, discrete geometry, and quantum information theory. In applications, solving semidefinite programs can still be a challenge.
The aim of this workshop is to bring together researchers working on applications and researchers working on solution methods for semidefinite programming and the broader field of convex nonlinear optimization. During the week we will have tutorial talks, research talks, discussions, and open problem sessions.