Tengyue (Olivia) Zhang
PhD Candidate in Bioengineering · UCLA
I am a PhD candidate in Bioengineering at UCLA, advised by Dr. William Hsu in the Hsu Lab. My research focuses on multimodal learning, generative models, and computational pathology. I develop machine learning methods that combine complementary medical data and improve how models generalize across imaging domains, with applications to cancer prognosis and medical image analysis.
Previously, I earned a B.S. in Computer Science and a B.A. in Gender Studies at UCLA. As an undergraduate, I worked with Dr. William Hsu on multimodal approaches to cancer prognosis and with Dr. Demetri Terzopoulos on medical image segmentation.
News
- September 3, 2026: Advanced to PhD candidacy in Bioengineering at UCLA.
- August 14, 2026: Our paper, “Semi-Supervised Domain Adaptation with Latent Diffusion for Pathology Image Classification”, was accepted at IEEE Journal of Biomedical and Health Informatics (JBHI).
- May 26, 2026: Presented “Target-Aware Domain Adaptation for Pathology Image Classification via Latent Diffusion Models” at UCLA Bioengineering Research Day.
- February 3, 2026: Awarded the UCLA Bioengineering Graduate Fellowship for Spring 2026.
- April 20, 2025: Our paper, “Evaluating an information theoretic approach for selecting multimodal data fusion methods”, was accepted at Journal of Biomedical Informatics.
- April 2025: Presented “Predicting Tumor Infiltration in Myxofibrosarcoma Using Whole-Slide Images” as a poster at IEEE ISBI 2025.
Research interests
- Multimodal learning for medical data
- Generative models and domain adaptation
- Computational pathology and cancer prognosis
Contact
Email: olivia [dot] zhang [at] ucla [dot] edu