报告题目：Single-Cell Computational Intelligence: New Tools for Autoimmune Disease Translational Medicine
报告人：张帆 美国科罗拉多大学 助理教授
报告摘要：
Chronic inflammation is a defining feature of immune-mediated inflammatory diseases, which collectively represent major causes of global disability and mortality. Progress in prevention and treatment has been limited in part by an incomplete understanding of disease-relevant immunophenotypes at molecular and cellular resolution. Recent advances in single-cell and spatial omics technologies now enable unprecedented profiling of immune cell states, but the scale, complexity, and heterogeneity of these datasets present major analytical challenges. In this talk, I will present our lab's interdisciplinary efforts to address this gap through the development of computational machine learning methods for large-scale single-cell multi-omics analysis in autoimmune diseases. I will highlight recent advances from our group, including the construction of a comprehensive single-cell atlas of rheumatoid arthritis (Nature, Science Translational Medicine), the development of disease prediction models that link immune states to clinical phenotypes (Journal of Clinical Investigation), and novel bioinformatics approaches for longitudinal single-cell modeling to capture temporal immune dynamics and spatial niches (Bioinformatics Advances, Briefings in Bioinformatics, etc). Together, our work demonstrates how single-cell computational intelligence bridges systems immunology and translational medicine, highlighting the potential of AI-driven single-cell approaches to accelerate translational medicine.
报告人简介：
张帆教授现为美国科罗拉多大学安舒茨医学院（University of Colorado Anschutz Medical Campus）生物医学信息学系健康人工智能中心和风湿免疫科的tenure-track 助理教授及课题组负责人。张教授于2012年在吉林大学计算机科学与技术学院完成本科和硕士学习，师从梁艳春教授。随后于2017年获得美国伍斯特理工学院（Worcester Polytechnic Institute）博士学位。2017–2021年在美国哈佛大学医学院及Broad Institute of Harvard/MIT从事博士后及研究科学家工作。于2022年在科罗拉多大学建立独立实验室。作为项目负责人获得NIH R01项目、团队科学领导学者项目等，及来自 NIH 妇女健康办公室和数据科学战略办公室的资助。张教授课题组致力于交叉研究，融合人工智能、计算生物学、单细胞组学与临床免疫学，开发面向自身免疫性疾病的计算方法，为新型治疗靶点发现和疾病预测模型构建提供了关键理论与技术支撑，推动基础发现向转化医学和精准医学应用。以第一或通讯作者在 Nature、Nature Immunology、Science Translational Medicine、Journal of Clinical Investigation、Genome Biology、Bioinformatics等国际顶级期刊发表多篇论文，总引用次数超过 15,000 次。她同时担任 Nature、Nature Medicine、Nature Communications、Nature Computational Science等期刊的审稿人，并在 ACR、ISMB 等国际会议上作大会报告和特邀报告。张教授课题组现招收全额奖学金博士研究生及访问学者。
报告时间：2026年2月2日（星期一）上午10：00
报告地点：吉林大学正新楼三楼智慧教室
