Bijan Afsari

Bijan Afsari serves as a Research Scientist at the Center for Imaging Science within the Johns Hopkins University Vision Lab, where he develops advanced statistical and computational frameworks for non-Euclidean spaces including Riemannian manifolds and Lie groups, with direct applications to computer vision, medical imaging, control theory, and structural biology.

He received his Ph.D. from the University of Maryland, College Park in 2009, completing a dissertation titled "Means and averaging on Riemannian manifolds" that established foundational work for his research trajectory.

Dr. Afsari's research focuses on theoretical and applied challenges in geometric statistics, particularly addressing averaging, clustering, and optimization in curved spaces where conventional Euclidean methods fail. His work provides critical mathematical tools for analyzing dynamic visual scenes, biological structures, and complex dynamical systems through rigorous non-linear frameworks.

His publication record demonstrates consistent innovation in bridging pure mathematics with engineering applications, notably through algorithms for joint diagonalization in blind source separation, convergence analysis of manifold-based optimization, and statistical properties of centers of mass in non-Euclidean geometry, disseminated across top mathematics and signal processing venues.

No scientific awards or honors are documented in the available information.

While specific student mentorship details are absent, his collaborative publications with researchers like René Vidal and R. Tron indicate active interdisciplinary engagement, though no research grants are explicitly referenced.

As a core member of the Johns Hopkins University Vision Lab, Dr. Afsari contributes to an interdisciplinary research ecosystem advancing computer vision through mathematical innovation within the Center for Imaging Science.