Biography
Dr. Haoyang Li is an Assistant Professor and Ph.D. advisor in the Department of Artificial Intelligence, School of Engineering, Westlake University. He received his B.Eng. (2018) from the College of Software, Jilin University, and his M.S. (2021) from the College of Computer Science and Technology, Jilin University. He obtained his Ph.D. in Computer Science (2025) from King Abdullah University of Science and Technology (KAUST), Saudi Arabia. During his doctoral studies, he was a visiting scholar at Yale University and Stanford University in the United States. From 2025 to 2026, he conducted postdoctoral research at Stanford University School of Medicine.
Research
Dr. Li's research is organized around AI Virtual Organ (AIVO): a generative computational counterpart of a real patient's organ, on which the questions that cannot be asked of the patient are asked in silico. It grows along a strictly hierarchical capability axis, from descriptive (what is the organ now) to predictive (what happens next, and under perturbation) to prescriptive (what should we do). His group advances this vision along five parallel fronts:
(1) Multimodal Spatial Biology. Aligning and translating across H&E, spatial omics, medical imaging, and clinical text, so that expensive or physically unmeasurable modalities can be inferred from the cheapest and most ubiquitous projection of tissue.
(2) 3D Spatial Biology. Reconstructing whole-organ three-dimensional volumes from two-dimensional sections, and modeling the emergence from molecule to cell to niche to tissue.
(3) Physical Spatial Biology. Encoding mechanics, conservation laws, and transport as priors, so that the virtual organ is not merely visually plausible but physically self-consistent.
(4) Temporal Spatial Biology. Turning destructive snapshots into continuous trajectories, and predicting how tissue evolves under time, injury, and perturbation.
(5) Downstream applications. Precision oncology, in silico drug screening, tissue aging, and regenerative medicine, each turning something previously unmeasurable or untestable into something computable.
Dr. Li has published 20+ peer-reviewed papers in leading journals and conferences, including Nature Machine Intelligence, Nature Communications, Science Advances, Bioinformatics, IEEE Transactions on Medical Imaging (TMI), and MICCAI, with eight first-author publications—among them multiple papers in Nature Communications (2023, 2024, 2025), Bioinformatics (2022), and MICCAI (2020). One first-author paper in Nature Communications was selected as an Editor’s Highlight and ranked among the Top 50 in “Biotechnology and Methods.” Dr. Li serves as Associate Editor and Guest Editor for journals such as Frontiers in Public Health and BMC Bioinformatics, and as a reviewer for Nature Biomedical Engineering, Nature Communications, Genome Biology, Genome Research, Bioinformatics, and major conferences including ICML, NeurIPS, ICLR, and MICCAI.
Representative Publications
1. Haoyang Li; Qinan Hu; Zhaowen Qiu; Hui Xiong; Yuhui Hu; Xin Gao; STP: single-cell partition for subcellular spatially-resolved transcriptomics, Nature Communications, 2025, 16(1): 4665
2. Haoyang Li; Yingxin Lin; Wenjia He; Wenkai Han; Xiaopeng Xu; Chencheng Xu; Elva Gao; Hongyu Zhao; Xin Gao; SANTO: a coarse-to-fine alignment and stitching method for spatial omics, Nature Communications, 2024, 15(1): 6048
3. Haoyang Li; Juexiao Zhou; Zhongxiao Li; Siyuan Chen; Xingyu Liao; Bin Zhang; Ruochi Zhang; Yu Wang; Shiwei Sun; Xin Gao; A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics, Nature Communications, 2023, 14(1):1548 (Editor’s Highlight)
4. Haoyang Li; Hanmin Li; Juexiao Zhou; Xin Gao; SD2: spatially resolved transcriptomics deconvolution through integration of dropout and spatial information, Bioinformatics, 2022, 38(21): 4878-4884
5. Haoyang Li; Juexiao Zhou; Yi Zhou; Jieyu Chen; Feng Gao; Ying Xu; Xin Gao; Automatic and interpretable model for periodontitis diagnosis in panoramic radiographs, Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020, Lima, Peru (virtual).
Contact Us
Email: lihy@westlake.edu.cn
Prof. Li's group continuously welcomes outstanding candidates at all levels, including postdoctoral researchers, Ph.D. students, research assistants, and visiting students. Applications are encouraged from diverse backgrounds (including but not limited to mathematics, physics, statistics, computer science, medicine, and biology). The group's research is directed toward the construction of AI Virtual Organs, focusing on multimodal, three-dimensional, physical, and temporal spatial biology, and aims to move beyond the inherent limits of observational research toward the prediction of disease evolution and individualized decisions on intervention. Taken together, the group builds generative, physics-informed models capable of translating across modalities, reconstructing organs in three dimensions, and extrapolating tissue states along the axes of time and perturbation. We therefore welcome applicants with a strong foundation in machine learning (generative modeling, representation learning, graph and geometric deep learning), applied mathematics or physics (optimal transport, differential equations, continuum mechanics), or quantitative biomedical science (spatial omics, pathology, medical imaging). Research projects are designed individually for each student, considering their research interests, background, and personal strengths.
Prospective applicants are invited to email lihy@westlake.edu.cn with the subject line: University + Name + (Ph.D./Postdoc/Visiting Student/RA Application), and attach a CV, personal statement, and any supporting materials.
