Ranit Karmakar

This paper introduces a computational pipeline combining image processing and machine learning to segment and quantify kidney tissue structures using Normalized Raman Imaging, achieving high segmentation performance.

The paper introduces an open-source pipeline for calcium imaging and all-optical physiology in human stem cell-derived neurons, validated for disease modeling and therapeutic screening.

This paper introduces NoRI, a Raman imaging technique that enables quantitative, label-free analysis of kidney tissue, revealing sex-specific differences and dynamic changes in acute kidney injury.