Research / Projects
A collection of our past and recently completed projects and publications.
A glucose prediction model for diabetes based on Deep Evidential Regression
A novel uncertainty-aware Physics-Informed Neural Network for scientific discoveries
A novel active learning method for biomedical image segmentation
Deep evidential regression for radiotherapy dose prediction
A Evidential Learning-based framwork for segmentation in MRI images
Modeling biochemical reaction pathways for ultra-high-dose-rate radiotherapy
A neural network-based model inference of cosmological parameters from astrophysical datasets
Fourier Neural Networks for predicting aircraft engine faults
Modeling shadows of rotating black holes in Einstein’s theory of general relativity
