Yuji Zhao

Cross-disorder Learning of Imaging-derived Joint Mophometric Markers in Alzheimer's and Parkinson's Diseases

As two most prevalent neurodegenerative diseases (NDDs), Alzheimer's disease (AD) and Parkinson's disease (PD) shared commonalities both in symptomology and pathophysiology. However, to what...

Morph-Transformer: A Deep Spatiotemporal Framework for Shape Analysis in Longitudinal Neuroimaging

Spatially Adaptive Morphometric Knowledge Transfer Across Neurodegenerative Diseases

Towards DTCO in High Temperature GaN-on-Si Technology: Arithmetic Logic Unit at 300 °C and CAD Framework up to 500 °C

Conditional Neural ODE for Longitudinal Parkinson's Disease Progression Forecasting

InGaN-based solar cells for space applications

Learning Interpretable Regularized Ordinal Models from 3D Mesh Data for Neurodegenerative Disease Staging

A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry

Constraining Disease Progression Models Using Subject Specific Connectivity Priors

A point of care electrochemical impedance spectroscopy device

GaN E-mode Complementary Transistors Based on a GaN-on-Si Platform Operational at 350°C

Record High Temperature Performance in Scaled AlGaN/GaN-on-Si HEMTs up to 500°C

Conditional Neural ODE for Longitudinal Parkinson's Disease Progression Forecasting

Parkinson's disease (PD) shows heterogeneous, evolving brain-morphometry patterns. Modeling these longitudinal trajectories enables mechanistic insight, treatment development, and individualized...