Mingze Dong
I received my Ph.D. in Computational Biology from Yale University, where I was co-advised by Prof. Yuval Kluger and Prof. Rong Fan. Before Yale, I earned my B.S. from Peking University, focusing on applied mathematics and biology.
I am currently a postdoctoral fellow at Stanford University before launching into independence. I am also building foundation models for biology at Arc.
I believe AI has enormous potential to transform biology, but the field has yet to achieve a true GPT moment. I think the gap is not just scale: it reflects limited biological data, the direct adoption of model architectures from other fields, and insufficient attention to what models actually learn — real biology versus batch effects, or generalization versus memorization.
My work approaches this question through large-scale AI, data science, and computational biology, with the goal of collecting the right data and building state-of-the-art models that help us understand, predict, and eventually design biological systems.
I am very happy to connect with people who share this vision and are excited about the opportunities ahead.
selected publications
- Preprint
- Nature MethodsCausal identification of single-cell experimental perturbation effects with CINEMA-OTNature Methods, 2023
- PreprintScaling deep identifiable models enables zero-shot characterization of single-cell biological statesbioRxiv, 2024
- Nature Commun
Editor’s HighlightSIMVI disentangles intrinsic and spatial-induced cellular states in spatial omics dataNature Communications (Featured Article, <5%), 2025 - Nature Methods
- NeurIPSUnderstanding and enhancing mask-based pretraining towards universal representationsThe Thirty-Ninth Annual Conference on Neural Information Processing Systems, 2025
- ICMLTowards Understanding and Reducing Graph Structural Noise for GNNsProceedings of the 40th International Conference on Machine Learning, 2023