Biography
Zitong (Jerry) Wang earned his Bachelor of Health Sciences from McMaster University before completing his Ph.D. in Systems Biology with a minor in Applied and Computational Mathematics at Caltech in 2024. At Caltech, he worked with Matt Thomson on AI methods to predict cancer therapies using multiplexed tumor imaging. Jerry also collaborated with Romain Lopez and Aviv Regev at Genentech, developing a contrastive learning framework for high-content CRISPR perturbation screens. Following his Ph.D., Jerry joined Recursion, where he worked with Kian Kenyon-Dean and Oren Kraus on tools to optimize large-scale vision models. Jerry was selected for a Schmidt Fellowship by the Broad Institute. He will join Westlake University as an independent fellow in Winter 2024.
Research
Our body is a bustling ecosystem, where immune cells vigilantly patrol for invaders, fibroblasts rush to heal wounds, and stem cells shift between dormancy and activity in response to environmental cues. With the growing availability of high-dimensional data capturing the molecular states of millions of cells simultaneously, we are now better equipped to understand these dynamic processes. Our lab focuses on building mathematical models to explain how cells behave within tissues, developing algorithms to predict cell state transitions in vivo, using these predictive models to design perturbation strategies that reprogram living systems from diseased to a healthy state, and ultimately testing our predictions in 3D organoids and animal models.
To tackle the complexity of the human body, we work across multiple diseases and organs, applying tools from molecular biology, physics, chemistry, and computer science as necessary. Recent projects include identifying perturbations that drive T cell infiltration using explainable AI, predicting molecular drivers of tumor metastasis by applying optimal transport theory to multiplexed tissue imaging, and building generative DNA models for de novo design of plasmid sequences encoding user-specified functions.
Representative Publications(*Co-corresponding authors)
1. Wang, Z. J.*, Farooq, A. S., Chen, Y. J., Bhargava, A., Xu, A. M., & Thomson, M.* (2024). Identifying perturbations that boost T-cell infiltration into tumors via counterfactual learning of their spatial proteomic profiles. Nature Biomedical Engineering, in press. https://doi.org/10.1101/2023.10.12.562107
2. Wang, Z.J., Lopez, R., Huetter, J-C., Kudo, T., Yao, H., Hanslovsky, P., Hoeckendorf, B., Mohan, R.R., Richmond, D. & Regev, A. (2024) Multi-ContrastiveVAE disentangles perturbation effects in single cell images from optical pooled screens. In ICLR 2024 Workshop on Machine Learning for Genomics Explorations.
3. Wang, Z. J.*, & Thomson, M.* (2022). Localization of signaling receptors maximizes cellular information acquisition in spatially structured natural environments. Cell Systems, 13(7), 530-546.e12. https://doi.org/10.1016/j.cels.2022.05.004
4. Joly-Smith, E., Wang, Z. J., & Hilfinger, A. (2021). Inferring gene regulation dynamics from static snapshots of gene expression variability. Physical Review. E, 104(4). https://doi.org/10.1103/physreve.104.044406
Contact Us
Email: jerry@westlake.edu.cn
We are actively recruiting Postdocs and Research assistants, and are open to co-advising graduate students. Please reach out if you are interested!
