Joseph Kileel

Exploring the impact of computational algebra and data science, Joseph Kileel serves as an Assistant Professor in the Mathematics Department and a Core Faculty Member of the Oden Institute at the University of Texas at Austin. With a robust academic foundation, he earned his Ph.D. from UC Berkeley in 2017, followed by a postdoctoral research tenure at Princeton University from 2017 to 2020. Joseph's research interests lie at the intersection of applied mathematics and computational techniques, focusing on inverse problems in computer vision and imaging science. His work delves into the complexities of numerical tensor computations and the development of fast methods for tensor decomposition, which are crucial for advancing scientific imaging and data analysis. In addition to his research, Joseph is deeply committed to teaching and mentoring the next generation of mathematicians and scientists. His courses often integrate theoretical knowledge with practical applications, preparing students to tackle real-world challenges in data science and applied mathematics. Joseph's contributions to the field have been recognized through various publications and collaborations, reflecting his dedication to pushing the boundaries of mathematical research. His ongoing projects continue to explore innovative solutions in optimization theory and scientific imaging, aiming to enhance computational efficiency and accuracy.