Biomedical Engineering · AI · Medical Imaging
Rohan N. Dhamdhere
PhD Candidate — Georgia Institute of Technology & Emory University
Building AI tools that help predict cardiovascular risk from routine clinical data — retinal images, ECGs, echocardiograms, and CT scans — bridging the gap between machine learning research and clinical practice.
Open to work
Open to Healthcare/Industry Data Science roles worldwide, including in-person and remote opportunities.
25+ publications · 100+ citations · 3 patents (1 allowed, 2 pending)
Research areas
Focus
Multimodal Fusion for Transplant Rejection
Heart transplant rejection surveillance using complementary ECG and biopsy signals — from ECG foundation-model embeddings that reduce biopsy burden to gated EMB+ECG fusion that improves rejection risk prediction over biopsy-only modeling. Featured in a 2026 transplant abstract and an under-review manuscript.
Opportunistic CT & Hepatic Screening
Co-invented DeHFT/LARI: a deep learning system to quantify hepatic steatosis from low-dose coronary calcium CT acquired for routine screening — validated on 700 patients, published in Lancet eBioMedicine 2025, underpins allowed US patent.
Spatiotemporal Cardiac Modeling
STAR-Echo: transformer-based spatiotemporal analysis of echocardiogram videos for MACE prognosis in CKD patients (MICCAI 2023), underpinning a pending patent on transformer-based spatiotemporal medical analysis.
Retinal AI for Systemic Disease
Repurposing routine fundus photographs to predict cardiovascular, renal, and neurodegenerative risk — validated in >800 CKD patients (CARE-CKD, Kidney360 2025), supported by GRA Phase 1 commercialization award.
Selected publications
Recent work
Dhamdhere R, et al. “Longitudinal Electrocardiographic Surveillance for Cardiac Allograft Rejection After Heart Transplantation.”
Manandhar S, Dhamdhere R, et al. “Multimodal Fusion of Biopsy and Electrocardiogram Data for Rejection Risk Prediction After Heart Transplantation.”
Dhamdhere R, et al. “Fundus Photograph-Derived Computational Features Predict Risk of Cardiovascular Events in the Chronic Renal Insufficiency Cohort.”
Modanwal G, Dhamdhere R, et al. “Opportunistic hepatic steatosis assessment in low-dose coronary artery calcium CT using liver adipose-radiomic index (LARI).”
Dhamdhere R, et al. “STAR-Echo: A Novel Biomarker for Prognosis of MACE Using Spatiotemporal Analysis of Echocardiogram Videos in CKD Patients.”