Interdisciplinary Grant in Biostatistics
 


Fellows

Careers






FELLOWS

Current Fellows (2014-2015)

Daphne Tsoucas, Zachary McCaw, and Shirley Liao are first year students in the doctoral program. They are currently working on course work. Daphne is enrolled in the first semester doctoral core courses, BIO 230 Probability I, and BIO 232 Methods I. She is also taking epidemiology courses, a computing course, and BIO 227 Fundamental Concepts in Gene Mapping. Zack is taking similar courses, with the addition of a course in Dynamic & Stochastic Processes. Shirley is taking the doctoral core with a strong focus in epidemiology in her other course selections.

Matthew Goodman is a second year student in the doctoral program. He will be taking the departmental written qualifying exam in early 2015 and has completed the basic doctoral core, BIO 230 Probability I, BIO 232 Methods I, BIO 231 Inference I, and BIO 233 Methods II. He is currently taking BIO 235 Advanced Regression and Statistical Learning, and BIO 249 Bayesian Methodology. During the spring 2014 Matthew completed one of his dry lab rotations with Dr. Philip de Jager and Dr. Zongqi Xia. They developed a new project that systematically examines the cormorbidity burden associated multiple sclerosis severity by using a phenome wide association approach. He also worked on another project that examined health care utilization in multiple sclerosis using electronic health records. Both projects will result in publications. His wet lab rotation was also in Dr. de Jager's lab, assisting lab techs with sample processing, both DNA extraction from saliva and isolating peripheral blood mononuclear cells (PBMCs or white blood cells) from whole blood samples. His dry lab work over summer 2014 was with Dr. Tianxi Cai and Dr. Lori Chibnik. The goals of the project were to 1) develop understanding of neuropathology of Alzheimers, eementia & cognitive impairment, 2) identify risk factors for disease, 3) investigate the role of cognitive/neural reserve in these pathologies, and 4) identify patients who may benefit from early interventions.