Min Wang

Min Wang is an Assistant Professor in the Department of Mathematics at the University of Houston. He holds a Ph.D. in Mathematics from Texas A&M University, advised by Prof. Yalchin Efendiev. His research focuses on Multiscale Finite Element Methods, Deep Learning techniques, and Flow Dynamics in Porous Media. These areas intersect computational mathematics, reservoir engineering, and data-driven modeling.

Key research contributions include advancements in multiscale modeling for thin domains, neural network-based solutions for high-dimensional PDEs, and reduced-order methods for transport problems. His work bridges traditional numerical methods with modern machine learning approaches to address challenges in porous media flow and reservoir simulation.

• Education: Ph.D. in Mathematics, Texas A&M University (2017)

His publications highlight innovative applications of deep learning for state estimation and model reduction, along with generalized multiscale frameworks for fractured reservoirs. Ongoing research explores the synergy between deep learning and computational methods to enhance scalability and accuracy in complex systems.