Jocelyn Quaintance

University of Pennsylvania, California University of Pennsylvania

Papers

Total Citations

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About

Jocelyn Quaintance is a mathematician whose work bridges pure and applied mathematics, with a primary focus on differential geometry, Lie groups, and their intersections with machine learning and optimization. Her most-cited paper, "Differential Geometry and Lie Groups" (2020, 63 citations), offers a rigorous yet accessible treatment of these foundational topics, serving as a key resource for researchers in robotics, computer vision, and geometric deep learning. Quaintance also co-authored "Linear Algebra And Optimization With Applications To Machine Learning - Volume I: Linear Algebra For Computer Vision, Robotics, And Machine Learning" (2020, 5 citations), which provides a practical, application-driven approach to linear algebra for modern AI systems. Her work is notable for making advanced geometric concepts tangible for engineers and data scientists, helping to bridge the gap between abstract theory and real-world algorithmic design. While her citation count is still growing, Quaintance’s contributions are increasingly recognized in interdisciplinary communities, particularly for her ability to synthesize complex mathematical structures into tools that drive innovation in autonomous systems and machine learning. Her writing is praised for its clarity and depth, making her a valuable voice at the intersection of mathematics and technology.