We develop mathematical theories and algorithms that can be used in various applications.
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The CMME Lab focuses on developing breakthrough computational methods and their applications for digital/smart healthcare system.
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The MIDaS Lab aims to develop state-of-the-art machine learning and computing methods by tackling real-world data science problems.
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We develop mathematical models and theoretical tools for problems in the fields of epidemiology and biology.
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We develop physics-based, data-driven modeling and computing techniques for multi-physics and multi-scale problems in energy and environmental applications.
We develop novel computational algorithms and mathematical tools to address fundamental scientific and engineering problems. In particular, we consider Polygonal Staggered Discontinuous Galerkin methods, Polygonal mesh generation via machine learning, finite volume methods, adaptive FEM for elliptic and parabolic equations and their applications to Navier-Stokes equations.
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We study the fundamentals and applications of turbulence using computational fluid dynamics and deep learning.
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