Members

Deep learning applied to data augmentation and segmentation tasks in medical image analysis with a primary focus on skin lesion images. 

Deep learning for medical image reconstruction with a primary focus on diffuse optical tomography. 

Interaction analysis in 2/3D super-resolution microscopy to discover new biological functions driving infectious and degenerative diseases, with a focus on belief theory in the context of weakly supervised object detection. 

Weakly supervised object localization and counting, with a focus on agricultural applications.  

Explainable AI with a focus on medical imaging tasks.

Deep learning applied to fluorescence microscopy to help explain and quantify morphological changes to cellular domains, with a focus on discovering drug- and virus-induced biomarkers. 

Inferring 3D plant structure from 2D images. 

Investigating a time-to-harvest application of deep neural nets for cannabis cultivation. 

Detection and segmentation of tumors in 3D PET/CT scans with domain knowledge inspired deep learning. 

Graph neural networks for super-resolution microscopy point cloud data analysis for understanding biological structures.

Artificial intelligence for health application.

Artificial intelligence for health application. 

Artificial intelligence for health application. 

Machine learning and computer vision applied to processes in agriculture and plant science. 

Super-resolution microscopy analysis of the endoplasmic reticulum. 

3D textured mesh analysis via deep learning for dermatology.