报告内容：Statistical and Computational Approaches for Analyzing Biobank Data
报告人：周华 副教授
报告时间：12月18日 10:00
报告地点：现代交通工程中心7950会议室
报告人简介:
周华，现任加州大学洛杉矶分校公共卫生学院生物统计系副教授,博士生导师。获中国医科大学临床医学学士学位，爱荷华州立大学生物信息和计算生物学硕士学位，和斯坦福大学统计学博士学位。研究方向包括大数据计算，神经图像处理，统计遗传学，个性化医疗，和干细胞建模。现任应用统计年鉴，美国工业与应用数学协会数据科学丛书等杂志编委。
报告内容简介:
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.
