Pushing the frontier of healthcare AI.
I am Dani Kiyasseh, an applied scientist who has spent the last 8 years building AI models across the healthcare continuum.
Research
Publications in ICML, NeurIPS, Nature Biomedical Engineering, and Nature Communications on surgical AI and clinical machine learning.
→Experience
From Oxford PhD to Caltech postdoc to founder — across academia, industry, and startups including Mayo Clinic, Flatiron Health, and Vicarious Surgical.
→Writing & Blog
Long-form posts on surgical AI, clinical deep learning, and the ideas behind the research — written for scientists and builders alike.
→Decoding surgeon activity from video.
A vision transformer that tracks surgical activity from operating room videos — featured on the front cover of Nature Biomedical Engineering. Developed during my postdoctoral fellowship at Caltech.
Read the paper →
From Oxford thesis to founder.
I have been operating at the intersection of AI and healthcare for the past 8 years. My recent focus has been on building large-scale vision-based foundation models to better understand surgery — a mission we started at Halsted AI, a Techstars-backed company I founded in 2025.
I completed my postdoctoral fellowship at Caltech, developing AI systems to track surgeon activity from videos. Before that, I received my PhD from the University of Oxford, where I developed deep learning models for limited labeled clinical data. I graduated from Johns Hopkins with a degree in biomedical engineering.
I was named to the Forbes 30 Under 30 and MIT Innovators Under 35 in the MENA region, and selected as a Rising Star in Engineering in Health by Columbia, Cornell, and Johns Hopkins. I have conducted AI research at Ford Motor Company, the Mayo Clinic, Merck, Flatiron Health, and Vicarious Surgical.
Selected work.
Across research, recognition, and building.
Let's connect.
Book a 1-hour consulting session on end-to-end AI development — from idea to production. Or reach out about surgical AI, research collaborations, and building in health.