Anuj Srivastava

Anuj Srivastava is a Professor in the Department of Statistics at Florida State University. His research focuses on statistical shape analysis, computational geometry, and their applications in medical imaging, computer vision, and machine learning. He develops novel methods for analyzing complex shapes, trajectories, and functional data, with particular emphasis on elastic geometry and manifold-based techniques.

Key research themes include shape analysis of 3D objects, brain subcortical structures, and tree-like anatomical networks. His work integrates statistical theory with computational tools to address challenges in biomedical imaging, motion tracking, and data-driven modeling. Notable contributions include frameworks for longitudinal elastic shape analysis (LESA), graph-based mobility modeling, and Bayesian emulation of human motion.

Recent projects involve NSF-funded collaborations on stochastic shape processes, pandemic simulation (RAW-ALPS), and statistical analysis of chromosome conformations. His methods are applied to diverse domains such as neuroimaging, cell morphology analysis, and electrical load profiling. The research emphasizes interdisciplinary applications with clinical, environmental, and engineering relevance.