AI researcher · Palo Alto
I work in radiology AI to help radiologists save time.
Lead or senior author in Nature, Nature Medicine, Nature Biomedical Engineering, ACL, EMNLP, NeurIPS and ICLR.
Long-form reading notes on radiology AI papers, with a focus on report generation.
RadAlign trains a small classifier, then lets an off-the-shelf LLM write the chest X-ray report from its predictions and seven retrieved reports. What the LLM is told about the image, and what the GREEN gain over a 2021 baseline is made of.
A model writes one sentence per lesion on whole-body PET/CT, guided by a predicted anatomical location. Its captions reach a BLEU-4 of 76.9 while its own word-matching check puts CT-finding accuracy at 67.3%: a lesson in how to score lesion-level reports.
A small vision–language model writes pathology reports for melanocytic skin lesions, and one pathologist scores 50 of them blind against the originals: level on ordinary moles, far behind on the other lesions. How far that evidence goes.
