Dr. Kiran Kumar Vupparaboina is a Research Assistant Professor of Ophthalmology at the University of Pittsburgh School of Medicine. With over a decade of experience in biomedical image processing, artificial intelligence, and medical imaging, Dr. Vupparaboina has made significant contributions to the field of ophthalmology. His expertise lies in developing AI-driven diagnostic tools for early detection and progression prediction of retinal diseases, particularly age-related macular degeneration (AMD), through the use of optical coherence tomography (OCT) imaging.
Dr. Vupparaboina has been closely working with clinicians and healthcare professionals to build quantitative imaging and image analysis solutions that enable more effective screening, treatment planning, and disease management. His work has been published in over 70 engineering and clinical research papers, and he has received competitive funding, including the prestigious Hillman Challenge Grant.
In addition to his academic research, Dr. Vupparaboina is the co-founder of Netramind Innovations, a company focused on commercializing AI-based solutions for personalized eye care. His mission is to improve patient outcomes and revolutionize ophthalmic diagnostics through cutting-edge technology and collaboration with industry leaders.
Detection of Disease Features on Retinal OCT Scans Using RETFound. Du K, Nair AR, Shah S, Gadari A, Vupparaboina SC, Bollepalli SC, Sutharahan S, Sahel JA, Jana S, Chhablani J, Vupparaboina KK. Bioengineering (Basel). 2024 Nov 25;11(12):1186. doi: 10.3390/bioengineering11121186.
Assessment of choroidal vessels in healthy eyes using 3-dimensional vascular maps and a semi-automated deep learning approach.Valsecchi N, Sadeghi E, Davis E, Ibrahim MN, Hasan N, Bollepalli SC, Singh SR, Fontana L, Sahel JA, Vupparaboina KK, Chhablani J. Sci Rep. 2025 Jan 3;15(1):714. doi: 10.1038/s41598-025-85189-7.
Inter-rater reliability in labeling quality and pathological features of retinal OCT scans: A customized annotation software approach. Du K, Shah S, Bollepalli SC, Ibrahim MN, Gadari A, Sutharahan S, Sahel JA, Chhablani J, Vupparaboina KK. PLoS One. 2024 Dec 18;19(12):e0314707. doi: 10.1371/journal.pone.0314707. eCollection 2024.
Three-Dimensional Choroidal Vessels Assessment in Age-Related Macular Degeneration. Sadeghi E, Valsecchi N, Ibrahim MN, Du K, Davis E, Bollepalli SC, Vupparaboina KK, Sahel JA, Chhablani J. Invest Ophthalmol Vis Sci. 2024 Nov 4;65(13):39. doi: 10.1167/iovs.65.13.39.
Optical Coherence Tomography Study of Choroidal Response to Exercise-Induced Hypertension in Chronic Central Serous Chorioretinopathy. Samanta A, Gregori G, Muzi A, Gujar R, Mariotti C, Fruttini D, Vupparaboina KK, Chhablani J, Nicolò M, Eandi CM, Cardillo Piccolino F, Lupidi M. J Clin Med. 2024 Nov 1;13(21):6580. doi: 10.3390/jcm13216580.
Dr. Kiran Vupparaboina's research is centered on leveraging artificial intelligence and medical imaging technologies to advance the early diagnosis and treatment of retinal diseases. His current work at the University of Pittsburgh focuses on two main areas:
1. Digital Twin of the Eye: This project aims to develop AI-based predictive analysis tools using longitudinal multimodal data, including patient vitals, demographics, and social determinants of health (SDoH). Dr. Vupparaboina and his team have created a centralized data management system that enables clinicians and researchers to access and analyze diverse datasets through a single interface. These efforts are geared toward improving patient-specific diagnosis, monitoring, and treatment outcomes, particularly for retinal conditions like AMD.
2. Choroid Analysis and Research (CAR) Lab: As part of the CAR Lab, Dr. Vupparaboina focuses on choroidal biomarkers, which are next-level indicators for early detection of retinal diseases. His team has developed AI tools for quantifying choroidal thickness and structure from OCT images, which have been widely used in clinical studies. These tools aim to improve the understanding of choroid-related diseases and provide clinicians with actionable insights for early intervention.