Computational Medical Imaging Laboratory (CMIL) develops novel computational methods to study and understand tissue micro-anatomy using digital brightfield microscopy histology and cutting-edge spatial-omics data. Methods developed by CMIL team inform clinical diagnostics and allow for the study of the fundamentals of biological systems. Currently, major focus of CMIL is diabetic kidney disease, kidney transplant, and normal reference kidneys in humans.

Overview of Research at CMIL.
We, humans, are built of hundreds and trillions of cells. The human systems can be measured at atoms to anatomical scale using a plethora of modern medical imaging and sequencing technologies. The resulting data need to be harnessed to understand what is normal reference and the intersection between normal and disease to better understand the disease. Microscopy plays a huge role in such assessment. CMIL studies multi-modal and multi-omics microscopy image data using cutting-edge AI tools to understand human systems. We ask fundamental questions using AI via quantifying cell morphology and interaction of the same measured via microscopy to answer various fundamental questions in biology and clinical science.


  • Digital & Computational Pathology
  • Microscopy Image Analysis
  • Image Processing
  • Multi-Omics Data Fusion
  • End-User Cloud Tool Development