Mathematical Modeling, Scientific Computing, and Data-Driven Discovery for Complex Biological Systems

I develop mechanism-informed and data-driven mathematical models, thermodynamically consistent formulations, and structure-preserving computational methods for complex systems involving fluid flow, ionic transport, osmotic effects, interfacial dynamics, and biological regulation.

My research connects applied mathematics with computational biology, biophysics, biomedical data science, and engineering applications. A central goal of my work is to translate physical and biological mechanisms into mathematically tractable models and reliable computational tools.

Research Contributions

Multiphysics Modeling and Structure-Preserving Computation

I develop thermodynamically consistent models and energy-stable numerical methods for complex fluids, semi-permeable and reactive interfaces, electrohydrodynamics, moving contact lines, and multiscale ion transport. This work combines continuum modeling, energy-based derivations, mathematical analysis, and high-fidelity scientific computation.

Neurovascular, Glymphatic, and Microcirculation Modeling

I develop multidomain models that couple blood flow, electrodiffusion, osmotic water transport, cellular regulation, and tissue-scale transport. Current applications include optic-nerve microcirculation, oxygen delivery, potassium clearance, neurovascular coupling, and glymphatic function.

Scientific Machine Learning and Translational Data Science

I develop robust and interpretable learning methods for noisy and imbalanced scientific data, physics-informed neural networks, biomedical signal reconstruction, disease-risk assessment, retinal-image analysis, and industrial optimization. My work emphasizes the integration of mathematical structure, physical mechanisms, and data-driven learning.

Current Research Directions

Current projects include mechanism-informed modeling of ocular neurovascular microcirculation, neurovascular–glial coupling, active and reactive transport across biological membranes, scientific machine learning for complex PDE systems, and mathematical modeling for biomedical and global-health applications.

Academic Leadership and Mentoring

I actively organize interdisciplinary workshops and research programs connecting mathematics, computation, life sciences, medicine, and engineering. I have supervised research scientists, graduate students, and undergraduate researchers working across mathematical modeling, scientific computing, machine learning, and biomedical applications.