Pak-Wing Fok

Pak-Wing Fok is a Professor in the Department of Mathematical Sciences at the University of Delaware, within the College of Arts & Sciences.

• M.Sci. - Imperial College
• Ph.D. - Massachusetts Institute of Technology
• Postdoctoral - California Institute of Technology
• Postdoctoral - University of California, Los Angeles

As an applied mathematician, Dr. Fok uses mathematical models to gain insight into complex problems from biology and the physical sciences, with a particular focus on cardiovascular diseases. His research spans multiple areas:

• Mathematical Modeling of Cardiovascular Systems: He investigates atherosclerosis and diabetes-related vascular complications, focusing on how mechanical properties and geometry of arteries change in these diseases. His work helps understand how plaque formation and rupture can lead to myocardial infarction or stroke.
• Mechanics of Growth: This research involves modeling biological systems where growth is a dominant feature, such as diseased blood vessels and bacterial chains. He studies how tissues undergo volumetric growth or resorption under mechanical deformation.
• MRI Parameter Estimation: He develops algorithms to improve parameter estimation in magnetic resonance imaging, addressing the challenge of inferring parameters from noisy signals in multi-component exponential functions.

Dr. Fok's recent publications reflect his interdisciplinary approach, combining mathematics, biology, and biomedical engineering. His work includes computational modeling of vulnerable plaques, stochastic processes in biophysics, and mathematical approaches to understanding vascular disease progression.

Dr. Fok has supervised numerous graduate students whose theses have focused on topics including:

• Simulation of Intimal Thickening
• Stochastic Modeling of Toxin Effects
• Finite Element Simulation of Atherosclerotic Plaque
• Estimation and Inference in Imaging and Biophysics
• Portfolio Theory Applications
• Analysis of Exit Time Problems

His methodology combines partial differential equations, asymptotic methods, stochastic analysis, and simulations to tackle complex problems in both biological systems and operations research.