Arjun is an undergraduate student volunteering with the lab. Deeply interested in the intersection of artificial intelligence and oncology, Arjun is working on developing an end-to-end computational pipeline that analyzes gigapixle whole-slide pathology images to quantitatively map the tumor microenvironment in endometrial cancer. The goal is to automate quality control to identify tissue artifacts and mormalize image stains so deep learning can segment and classify hundreds of thousands of individual cells into neoplastic, inflammatory, and stromal categories. This large-scale spatial data extraction is used to help build prognostic models that predict patient outcomes and treatment responses.
Arjun brings relevant experience to the Madabhushi Lab, having worked with the University of California San Diego Health, Radiology, Liver Imaging Group. Over the course of a summer internship in 2025, he designed and built a REDCap database for Bayer AG to support clinical studies evaluating gadoxetate-enhanced MRI (Gx-MRI) for focal liver lesions. Additionally, he conducted 9-region-of-interest (ROI) spatial analyses on MRI scans to extract proton density fat fraction (PDFF) and R2* values, performing comparative statistical evaluations to assess how patient positioning affects MRI-derived measurements.
Arjun is pursuing a BS degree In data science with a concentration in biology, and a minor in artificial intelligence from Emory University College of Arts and Sciences. He aims to graduate in 2028.