Ph.D. (Texas A&M University)

B.Eng. (Xi’an Jiaotong University)

Dr. Yuning You is an assistant professor at the School of Science and Engineering of The Chinese University of Hong Kong, Shenzhen. Dr. You received his Ph.D. degree from Texas A&M University (2019-2024), his B.Eng. degree from Xi'an Jiaotong University (2015-2019), and conducted postdoctoral research at the California Institute of Technology (2024-2025). In 2025, Dr. You received the Distinguished Graduate Student Award for Excellence in Research from the Association of Former Students at Texas A&M University. Dr. You's research focuses on developing machine learning algorithms for pattern analysis of structural data, including graphs, point clouds, and fields—specifically, he develops a branch of algorithms termed graph self-supervised learning for data mining on large-scale graph data of small molecules, protein contact maps, and single cells. By leveraging these algorithms, he is dedicated to building simulators for living systems at different scales, including molecules, cells, tissues, organisms, and clinical applications—he recently built a simulator termed "virtual tissues" to model the complex interactions among genes, cells, and niches. These simulators serve as effective computational tools for broad applications in life sciences research, such as drug discovery.

1. NeurIPS’20: “Graph Contrastive Learning with Augmentations”, Y. You#, T. Chen#, Y. Sui, T. Chen, Z. Wang, Y. Shen, Conference on Neural Information Processing Systems, pp. 5812-5823, 2020. (#Equal Contribution, Acceptance Rate 20.09%)

2. ICML’21 Long Presentation: “Graph Contrastive Learning Automated”, Y. You, T. Chen, Y. Shen, Z. Wang, International Conference on Machine Learning, pp. 12121-12132, 2021. (Acceptance Rate 3.01%)

3. Bioinformatics’22: “Cross-Modality and Self-Supervised Protein Embedding for Compound- Protein Affinity and Contact Prediction”, Y. You, Y. Shen, Bioinformatics, vol. 38(Supplement 2), pp. 68-74, 2022. (Impact Factor 6.93, MoML’22, ECCB’22 with Acceptance Rate 17.40%, 3DSIG COSI@ISMB/ECCB’21, MLSB@NeurIPS’20)

4. ICLR’23: “Graph Domain Adaptation via Theory-Grounded Spectral Regularization”, Y. You, T. Chen, Z. Wang, Y. Shen, International Conference on Learning Representations, oprev., 2023. (Acceptance Rate 31.80%)

5. ICLR’24: “Latent 3D Graph Diffusion”, Y. You, R. Zhou, J. Park, H. Xu, C. Tian, Z. Wang, Y. Shen, International Conference on Learning Representations, oprev., 2024. (Acceptance Rate 31.00%)

6. MLGenX’25: “Building Foundation Models to Characterize Cellular Interactions via Geometric Self-Supervised Learning on Spatial Genomics”, Y. You, Z. Wang, K. Fleisher, R. Liu, M. Thomson, Machine Learning for Genomics Explorations Workshop, International Conference on Learning Representations, 2025.