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Jia Zhao
Associate Professor
Ph.D., 2015, University of South Carolina
At Binghamton since 2023
Areas of Interest: Mathematical modeling, numerical analysis, high-performance computations, machine learning
Summary of research interests
E-mail: | jzhao10@binghamton.edu, jzhao10@math.binghamton.edu |
Office: | WH 126 |
Phone: | (607) 777-2516 |
Fax: | (607) 777-2450 |
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Courses:
Fall 2024
Math 329 | Section 01 : | Introduction to Scientific Computing |
| MWF 8:00 - 9:30 | CW-113 |
Math 488A | Section 01 : | Topics in Modern Math: Linear Algebra for Statistics |
| MWF 9:40 - 10:40 | CW-109 |
Math 530 | Section 01 : | Linear Algebra for Statisticians |
| MWF 9:40 - 10:40 | CW-109 |
Spring 2025
Math 329 | Section 01 : | Introduction to Scientific Computing |
| MWF 9:40 - 11:10 | - |
Math 590S | Section 01 : | Topics in Statistics |
| MWF 1:10 - 2:10 | WH-100E |
Ph. D. Students:
Personal Website
Research Interests
I am trained as an applied and computational mathematician, aiming to strike a balance between mathematical modeling, numerical analysis, and high-performance simulations, while my application domains are multiphase complex fluids and mathematical biology. My research is highly interdisciplinary, sitting at the interface between applied mathematics, scientific computing, soft matter physics, and mathematical biology. Here are several projects I have been working on:
Machine learning and deep neural networks on PDE model discovery
Computational modeling of how living cells utilize LLPS to organize chemical compartments
Hydrodynamic Models of Biofilms (biofilm formation, antimicrobial persistence, quorum sensing)
Modeling Eukaryotic Cell Mitotic Dynamics (mitotic rounding, cell oscillation, cell motility and cytokinesis)
Complex Fluids Model Development (multiphase fluids, active liquid crystals, viscoelastic fluids)
Fluid Structure Interactions (FSI) in Complex Fluids with Applications in Biology and Medicine
Modeling and Design of Multifunctional Polymeric Rod-like Nano-composites
Accurate, Efficient and Stable Numerical Schemes for Multiphase Complex Fluids Models
Deep Neural Network for solving Partial Differential Equations
Software Development on Hybrid CPU-GPU Architecture