Ulzee An
UCLA Computer Science Department / Computational Medicine
404 Westwood Blvd.
Los Angeles, CA 90025
Hi! I’m Ulzee. My name is based on a street of the same name in Korea (을지). I received my PhD in Computer Science with Professor Sriram Sankararaman from UCLA (May 2025). My research interests are in applying state-of-art machine learning methods to improve our understanding of complex diseases. My experience spans many modalities that are encountered in healthcare: genomics, doctors’ notes, X-rays, MRIs, motion sensors, and more.
Check out my academic CV or resume.
Before joining UCLA, I obtained an MS in Computer Science at NYU while researching traffic patterns with Professor Lakshmi Subramanian. I obtained my Bachelor’s in Computer Science at UIUC where I contributed to projects involving motion sensors in Professor Prashant Mehta’s lab.
Other things: I had a research internship with Uber in 2022 where I worked on probabilistic and DL embedding methods. See what I do for fun. Feel free to reach out to me at ulzee [at] cs [dot] ucla [dot] edu.
selected publications
- ICML
Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation ModelsIn Proceedings of the 42nd International Conference on Machine Learning (ICML), 2025Spotlight (Top 2.6%) - ICML
CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data ImputationIn Proceedings of the 42nd International Conference on Machine Learning (ICML) , 2025Spotlight (Top 2.6%) - Nature BME
Accurate prediction of disease-risk factors from volumetric medical scans by a deep vision model pre-trained with 2D scansNature Biomedical Engineering, 2024 - Nature Gen
Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorderNature Genetics, 2023 - Nature Gen
Deep learning-based phenotype imputation on population-scale biobank data increases genetic discoveriesNature Genetics, 2023
