報告內容：Statistical and Computational Approaches for Analyzing Biobank Data
報告人🧎🏻♀️：周華 副教授
報告時間：12月18日 10:00
報告地點：現代交通工程中心7950會議室
報告人簡介:
周華，現任加州大學洛杉磯分校公共衛生恒达生物統計系副教授,博士生導師。獲中國醫科大學臨床醫學學士學位🫥，愛荷華州立大學生物信息和計算生物學碩士學位🐃，和斯坦福大學統計學博士學位。研究方向包括大數據計算，神經圖像處理，統計遺傳學🧑🏽🏭，個性化醫療，和幹細胞建模。現任應用統計年鑒🧝🏽，美國工業與應用數學協會數據科學叢書等雜誌編委🐑。
報告內容簡介:
Dr. Zhou has long term interests in numerical optimization problems, particularly those arising from statistical analysis of high-dimensional data. He developed highly scalable optimization algorithms for maximum likelihood estimation of some multivariate discrete distributions, calculation of importance sampling weights for large data sets, geometric and signomial programming, and a model-based movie rating method. He also proposed a new deterministic annealing method for global optimization, a quasi-Newton scheme for accelerating high-dimensional optimization algorithms, and a strategy for massive parallel computing using graphical processing units (GPUs). He studied new path following algorithms for regularization problems in statistics and machine learning, and successfully generalized them to least angle regression and convex programming. His recent development also includes scalable estimation algorithm for multivariate response generalized linear models and variance components models, fast matrix computation tools, and distance majorization for convex programming.
