Allen Tannenbaum is an applied mathematician and presently Distinguished Professor of Computer Science and Applied Mathematics & Statistics at the State University of New York at Stony Brook. He is also an Affiliate Attending Computer Scientist of Medical Physics at Memorial Sloan Kettering Cancer Center in New York City. Dr. Tannenbaum has done research in numerous areas including robust control, computer vision, and biomedical imaging, having more than 500 publications. He pioneered the field of robust control with the solution of the gain margin and phase margin problems using techniques from Nevanlinna–Pick interpolation theory, which was the first H-infinity type control problem solved. He was one of the first to introduce partial differential equations in computer vision and biomedical imaging co-inventing an affine-invariant heat equation for image enhancement. Dr. Tannenbaum and collaborators further formulated a new approach to optimal mass transport (Monge-Kantorovich) theory. In recent work, he has developed techniques using graph curvature ideas for analyzing the robustness of complex networks. His work has won several awards including IEEE Fellow, O. Hugo Schuck Award of the American Automatic Control Council, and the George Taylor Award for Distinguished Research from the University of Minnesota. He has given numerous plenary talks at major conferences including the IEEE Conference on Decision and Control of the IEEE Control Systems Society, and the International Symposium on the Mathematical Theory of Networks and Systems (MTNS).