Overview
Shixin Xu is an Assistant Professor of Mathematics whose research spans several dynamic and interconnected fields. His primary interests include machine learning and data-driven models for disease prediction, multiscale modeling of complex fluids, neurovascular coupling, homogenization theory, and numerical analysis. His current projects reflect a diverse and impactful portfolio:
- Developing predictive models based on image data to identify hemorrhagic transformation in acute ischemic stroke.
- Conducting electrodynamics modeling of saltatory conduction along myelinated axons to understand nerve impulse transmission.
- Engaging in electrochemical modeling to explore the interactions between electric fields and chemical processes.
- Investigating fluid-structure interactions with mass transport and reactions, crucial for understanding physiological and engineering systems.
These projects demonstrate his commitment to addressing complex problems through interdisciplinary approaches that bridge mathematics with biological and physical sciences.
Current Appointments & Affiliations
Assistant Professor of Mathematics at Duke Kunshan University
·
2019 - Present
DKU Faculty
Assistant Professor of the Practice of DKU Studies at Duke University
·
2024 - Present
DKU Studies
Recent Publications
An imbalanced learning-based sampling method for physics-informed neural networks
Journal Article Journal of Computational Physics · August 1, 2025 This paper introduces Residual-based Smote (RSmote), an innovative local adaptive sampling technique tailored to improve the performance of Physics-Informed Neural Networks (PINNs) through imbalanced learning strategies. Traditional residual-based adaptive ... Full text CiteImproving GBDT performance on imbalanced datasets: An empirical study of class-balanced loss functions
Journal Article Neurocomputing · June 14, 2025 Class imbalance poses a persistent challenge in machine learning, particularly for tabular data classification tasks. While Gradient Boosting Decision Trees (GBDT) models are widely regarded as state-of-the-art for these tasks, their effectiveness diminish ... Full text CiteEnhanced friction and wear behavior of submicron WC-reinforced Cu matrix composites at various temperatures
Journal Article Journal of Materials Research and Technology · March 2025 Full text CiteEducation, Training & Certifications
University of Science and Technology of China (China) ·
2013
Ph.D.