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About

Baba C. Vemuri is a leading figure in computational geometry and robotics, whose work bridges the gap between theoretical mathematics and practical engineering. His research focuses on shape representation, motion estimation, and the statistical analysis of data lying on non-Euclidean spaces, such as Lie groups. A major contribution is his pioneering work on a novel FEM-based dynamic framework for subdivision surfaces (2000, 35 citations), which provided a powerful method for modeling deformable objects. In robotics, he developed techniques for motion estimation from multi-sensor data (2005, 14 citations) and invariant surface analysis from sparse range data (1992, 7 citations), enabling more robust perception for autonomous systems. More recently, his work on shrinkage estimation of the Fréchet mean in Lie groups (2020, 3 citations) addresses the critical challenge of analyzing orientation data from sensors, a problem central to modern robotics and computer vision. With foundational contributions dating back to object recognition from depth maps (1987), Vemuri’s career demonstrates a sustained commitment to solving complex geometric problems, making his research essential reading for students and engineers working at the intersection of geometry, statistics, and robotics.