Molei Tao

Professor advancing research in applied and computational mathematics, Molei Tao is an Associate Professor at the Georgia Institute of Technology's School of Mathematics. With a keen interest in utilizing mathematical tools such as nonlinear dynamics, probability, and geometry, Professor Tao is dedicated to addressing practical challenges through innovative approaches. His research is particularly focused on the realms of machine learning, where he delves into sampling, optimal transport, and generative modeling. In addition to his work in machine learning, Professor Tao is deeply engaged in the fields of deep learning, optimization, and scientific machine learning. His contributions to these areas are marked by a commitment to advancing the understanding and application of mathematical principles to solve complex problems. Through his research, he aims to bridge the gap between theoretical mathematics and real-world applications, fostering advancements that have the potential to impact various industries. Professor Tao's work is characterized by a blend of theoretical insight and practical application, making significant strides in the development of new methodologies and tools. His dedication to the field is reflected in his numerous publications and collaborations with fellow researchers, contributing to the broader scientific community's understanding of these complex topics. At Georgia Tech, Professor Tao is not only a researcher but also an educator, inspiring the next generation of mathematicians and scientists. His teaching philosophy emphasizes the importance of critical thinking and problem-solving skills, preparing students to tackle the challenges of the future with confidence and creativity. Through his mentorship, he continues to shape the future of mathematics and its applications in the modern world.