ope体育电竞_OPE电竞电竞游戏_ope官网 英超哈德斯菲尔德赞助

您的位置: 首页 >>  学术报告

Use Data to Build Differential Equation Models with Applications: Past, Current and Future


报告人: Prof. Hulin Wu



报告地点:长安校区 文津楼数学与信息科学学院学术报告厅



武虎林, 美国德克萨斯大学休斯顿健康科学中心公共卫生学院生物统计和数据科学系Betty Wheless Trotter教授,系主任,博士生导师。于1994年获博士学位。研究兴趣致力于大数据分析,微分方程模型的统计方法和理论,高维数据分析和推断,免疫数据分析与建模等, 在顶级国际统计学术期刊,如JASA, Biometrics, Biostatistics, Annals of Applied Statistics等发表论文多篇;特别是在HIV病毒动力学和细胞动力学建模方面,武教授是先驱者之一,在HIV病毒的适定性方面提出了新的数学模型和思想,这些重要的研究结果发表在权威生物医学期刊《Journal of Virology》和《Journal of Clinical Microbiology》上等。


Differential equations are widely used to describe dynamic processes and systems in many scientific fields such as engineering, physics, chemistry, social sciences, economy, biology and biomedical sciences. However, both model structures and model parameters need to be determined based on experimental data and mechanisms of the dynamic systems. It is very challenging to solve the inverse problems of differential equation models by rigorously using experimental data to develop and validate the differential equation models. In two lectures, I will go over statistical methodologies for parameter estimation and model evaluation of different ordinary differential equation (ODE) models that have been developed in the past decade by our group and other colleagues. This will include model parameter identifiability, model structure identification, parameter estimation, model validation and evaluation based on experimental data. Experimental data from recent studies from different fields will be used to illustrate the ODE modeling principles. The current status and future development for constructing differential equation models based on data will be discussed.



版权所有 © 陕西师范大学