张传超 博士
助理研究员
邮箱：chuanchaozhang@ucas.ac.cn
主要研究方向:
人工智能与机器学习，空间组学数据建模，单细胞数据建模，多组学数据整合建模
教育和工作经历:
2021.1-至今 国科大杭州高等研究院,助理研究员
2020.1 - 2021.1 上海脑科学与类脑研究中心 助理研究员
2017.8 - 2020.1 华为武汉研究所（架构、算法预研） 高级工程师
2011.9 - 2017.7 武汉大学(计算机软件与理论) 硕博
近三年主持或参加的基金项目/课题：
(1) 浙江省探索项目，多尺度时空表型绘制的理论与方法研究，2026-01-01 至 2027-12-31, 10万元, 在研, 主持
(2) 国家自然科学基金委员会, 青年科学基金项目, 62202120, 基于空间转录组数据的空间域识别与细胞类型推断建模研究, 2023-01-01 至 2025-12-31, 30万元, 在研, 主持
(3) 浙江省“尖兵”科技计划项目, 2025C01114, 面向重大疾病的计算生物学关键技术及应用, 2025-01-01 至 2026-12-31, 800万元, 在研, 参与
(4) 国家自然科学基金委员会, 数学天元基金项目, 12326614, 颅内肿瘤多模态数据融合的可通用诊疗模型及系统, 2024-01-01 至 2025-12-31, 80万元, 在研, 参与
(5) 国家自然科学基金委员会, 面上项目, 12271180, 基于时空信息转换的生物系统临界状态预警方法的研究, 2023-01-01 至 2026-12-31, 46万元, 在研, 参与
(6) 国家自然科学基金委员会, 重点项目, 12131020, 基于多模态数据的健康临界状态的数学刻画与预警理论, 2022-01-01 至 2026-12-31, 252万元, 在研, 参与
(7) 国家自然科学基金委员会, 数学天元基金项目, 12126605, 支持病理诊断自动化的数学理论、方法与系统, 2022-01-01 至 2023-12-31, 100万元, 结题, 参与
(8) 国科大杭州高等研究院，青苗计划，基于时空组学的癌症异质性建模研究，2023HIAS，主持，62万
(9) 指导学生获得2025年国科大杭州高等研究院创新创业甲类项目（资助金额20万元）
近三年学术论文:
[1] Zedong Wang, Bowen Fu, Chuanchao Zhang*, Xiaoping Liu*. Reconstructing Coherent Functional Landscape From Multi-Modal Multi-Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process. Advanced Science, 2026
[2] Xinyu Bao, Xiaosheng Bai, Xiaoping Liu*, Qianqian Shi*, Chuanchao Zhang*. Spatially informed graph transformers for spatially resolved transcriptomics. Communications Biology. (2025)
[3] Xiaosheng Bai, Xinyu Bao, Chuanchao Zhang*, Qianqian Shi*, Luonan Chen*. SpaDCN: Deciphering spatial functional landscape from spatially resolved transcriptomics by aligning cell–cell communications. Small Methods (2025): 2402111.
[4] Wendong Huang, Yaofeng Hu, Lequn Wang, Guangsheng Wu, Chuanchao Zhang*, Qianqian Shi*. Spatially aligned graph transfer learning for characterizing spatial regulatory heterogeneity. Briefings in Bioinformatics (2025) 26: bbaf021.
[5] Yiwen Yang#, Chengming Zhang#, Zhaonan Liu, Kazuyuki Aihara, Chuanchao Zhang*, Luonan Chen*, Wu Wei*. MCGAE: unraveling tumor invasion through integrated multimodal spatial transcriptomics. Briefings in Bioinformatics (2025) 26: bbae608.
[6] Lequn Wang, Xiaosheng Bai, Chuanchao Zhang*, Qianqian Shi*, Luonan Chen*. Spatially aware domain adaptation enables cell type deconvolution from multi‐modal spatially resolved transcriptomics. Small Methods (2024): 2401163.
[7] Lequn Wang, Yaofeng Hu, Kai Xiao, Chuanchao Zhang*, Qianqian Shi*, Luonan Chen*. Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics. Briefings in Bioinformatics (2024) 25: bbae257.
[8] Yaofeng Hu, Kai Xiao, Hengyu Yang, Xiaoping Liu*, Chuanchao Zhang*, Qianqian Shi*. Spatially contrastive variational autoencoder for deciphering tissue heterogeneity from spatially resolved transcriptomics. Briefings in Bioinformatics (2024) 25: bbae016.
[9] Chuanchao Zhang*, Lequn Wang, Qianqian Shi*. Computational modeling for deciphering tissue microenvironment heterogeneity from spatially resolved transcriptomics. Computational and Structural Biotechnology Journal (2024) 23: 2109-2115.
[10] Chuanchao Zhang, Xinxing Li, Wendong Huang, Lequn Wang*, Qianqian Shi*. Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification. Briefings in Bioinformatics (2023) 24: bbad197.
[11] Chengming Zhang#, Yiwen Yang#, Shijie Tang, Kazuyuki Aihara*, Chuanchao Zhang*, Luonan Chen. Contrastively generative self-expression model for single-cell and spatial multimodal data. Briefings in Bioinformatics (2023) 24: bbad265.
[12] Chengming Zhang#, Yabin Chen#, Tao Zeng*, Chuanchao Zhang*, Luonan Chen*. Deep latent space fusion for adaptive representation of heterogeneous multi-omics data. Briefings in Bioinformatics (2022) 23: bbab600.
