Weiruo Zhang
Assistant Professor of Computer Science
Assistant Professor of Computer Science
Dr. Weiruo Zhang earned her PhD in Electrical Engineering from Stanford University. Her research lies at the intersection of computation and cancer research, developing machine learning and AI methods that integrate spatial multi-omics, medical imaging and clinical data to study tumor progression and improve cancer treatment. Dr. Zhang created CELESTA, a widely adopted machine learning tool to identify cell types in tissue samples, which has been embraced… ↓More
Joined department: Fall 2025
Research Areas
- Artificial Intelligence, Machine Learning, and Natural Language Processing
- Bioinformatics and Computational Biology
Education
PhD, Stanford University, Electrical Engineering
MS, Stanford University, Electrical Engineering
BS, National University of Singapore, Electrical Engineering (honorary)
Dr. Weiruo Zhang earned her PhD in Electrical Engineering from Stanford University. Her research lies at the intersection of computation and cancer research, developing machine learning and AI methods that integrate spatial multi-omics, medical imaging and clinical data to study tumor progression and improve cancer treatment.
Dr. Zhang created CELESTA, a widely adopted machine learning tool to identify cell types in tissue samples, which has been embraced by the research community and incorporated into commercial software by biotechnology companies. She also developed MONTAGE, a computational framework that integrates multi-modal data to study cellular organization in cancer tissues, revealing clinically relevant biological functions embedded in their spatial architecture.
Her work has been published in leading journals including Nature Methods, Science Immunology and Cell, and continues to advance both computational methods and biological discovery in cancer research.
Selected Publications
W. Zhang, I. Li, N. Reticker-Flynn, Z. Good, S. Chang, N. Samusik, S. Saumyaa, X. Zhou, Y. Li, R. Liang, C. Kong, Q.T. Le, J. Sunwoo, A. Gentles, G. Nolan, E. Engleman, S. Plevritis, “Identification of cell types in multiplexed in situ images by combining protein expression and spatial information using CELESTA”, Nature Methods, 19(6):759-769, (2022)
N. Reticker-Flynn, W. Zhang, J. Belk, P. Basto, N. Escalante, G. Pilarowski, A. Bejnood, M. Martins, J. Kenkel, I. Linde, S. Bagchi, R. Yuan, S. Chang, M. Spitzer, Y. Carmi, J. Cheng, L. Tolentino, O. Choi, N. Wu, C. Kong, A. Gentles, J. Sunwoo, A. Satpathy, S. Plevritis, E. Engleman, “Lymph node colonization alters the systemic immune response to enable metastasis to distant tissues”, Cell, 185(11):1924-1942, (2022)
N. Li, W. Zhang, D. Haensel, A. Jussila, C. Pan, S. Gaddam, S. Plevritis, A. Oro, “Basal-to-inflammatory transition and tumor resistance via crosstalk with a pro-inflammatory stromal niche”, Nature Communications, 15:8134, (2024)
G. Bouchard, W. Zhang, I. Li, I. Ilerten, A. Bhattacharya, Y. Li, W. Trope, J. Shrager, C. Kuo, L. Tian, A. Giaccia, S. Plevritis, “A quantitative spatial cell-cell colocalizations framework enabling comparisons between in vitro assembloids and pathological specimens”, Nature Communications, 16:1392, (2025)
W. Zhang, G. Bouchard, A. Yu, M. Shafiq, M. Jamali, J. Shrager, K. Ayers, S. Bakr, A. Gentles, M. Diehn, A. Quon, R. West, V.S. Nair, M.V.D. Rijn, S. Napel, S. Plevritis, “GFPT2-expressing cancer-associated fibroblasts mediate metabolic reprogramming in human lung adenocarcinoma”, Cancer Research, 78(13):3445-3457, (2018)