Masha Bondarenko

I graduated from UC Berkeley with a degree in Electrical Engineering & Computer Science in 2024. I currently work as a deep learning researcher in the Sohn Lab at UCSF, where I collaborate with doctors and engineers to solve the biggest challenges within radiology diagnostics and workflows. My technical interests have spanned risk modeling (via vision FMs, diffusion/GANs, UNets) and have recently expanded into uncertainty quantification and adversarial analyses within clinical VLMs.

Research

Prediction of Interval Growth in Subsolid Pulmonary Nodules using Baseline CT and Longitudinal Interval

Oral Presentation | RSNA, 2026

Time-conditioned Estimation of Lesion Morphologic Evolution and Volumetric Growth in Subsolid Pulmonary Nodules using an Interval-embedded 3d model

Poster Presentation | RSNA, 2026

Prediction of Subsolid Pulmonary Nodule Evolution from Baseline CT Using Temporal Imaging Models

Planner-Executor Style Multimodal Agentic System to Answer Patient Questions in Lung Cancer Screening CT

Automated Detection of Interstitial Lung Abnormalities on Chest CT: Multi-Center Validation and Clinical Impact Evaluation

Imaging Biomarkers Predicting Progression of Interstitial Lung Abnormalities to Idiopathic Pulmonary Fibrosis: Multicontinental Validation Study

Investigating AI's potential in risk-stratifying lung cancer screenings for future follow-ups: A retrospective analysis of a tertiary hospital cohort

Detection of Interstitial Lung Abnormalities on Chest CT: Comparative Evaluation of Radiomics and Deep Learning Models

Radiological Society of North America Annual Meeting, 2025

Clinical and Imaging Factors Associated with Growth of Subsolid Pulmonary Nodule on CT

Radiological Society of North America Annual Meeting, 2023