Sanghyun Lee, PhD

Dr. Sanghyun Lee is an associate professor of mathematics at FSU. His research develops high-fidelity numerical methods and scientific machine learning for multiphysics and multiscale PDEs, focusing on subsurface applications like poroelasticity and fracture. He has published widely on finite element methods and is a co-PI on a DOE project for subsurface energy systems.

Lingjiong Zhu, PhD

Dr. Zhu is a professor and the Thinking Machines Eminent Scholar in Mathematics at FSU. As an applied probabilist, his research focuses on the theoretical study of stochastic algorithms for large-scale sampling and optimization problems in machine learning (AI). His work, which is applied to financial engineering, is published in top venues like NeurIPS and ICML.

Nick Dexter, PhD

Dr. Dexter is an assistant professor of scientific computing at FSU. His research focuses on computational mathematics, scientific machine learning, and uncertainty quantification, applied to areas like energy systems and deep learning. He has published at premier venues like NeurIPS and ICML and is passionate about advancing interdisciplinary research.

Adrian Barbu, PhD

Dr. Adrian Barbu is a professor in the Department of Statistics at FSU, holding PhDs in Mathematics and Computer Science. His expertise spans computer vision, machine learning, and medical imaging, resulting in over 90 papers and 25 patents. He is a recipient of the Thomas A. Edison Patent Award and the FSU Graduate Faculty Mentor Award.

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