We develop new experimental and analytical tools for 3D biological cell imaging that uniquely combine label-free wave-front sensing and imaging approaches, providing deep data by quantitative morphological and contents cellular imaging, and artificial intelligence (AI) by novel approaches for deep learning.

Current specific subjects of interest include:

• Deep-learning platforms for cell classification [Papers]

• Deep-learning platforms for cell virtual staining [Papers]

• Rapid label-free wave-front imaging and sensing of biological cells [Papers]

• Portable interferometric modules for clinical use [Papers]

• 3D refractive-index live-cell tomography [Papers]

• Interferometric nanoscopy [Papers]
  

Clinical Applications

• Sperm selection for IVF [Papers]

• Cancer cell analysis in liquid biopsies [Papers]