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Featured stories about UW Biostatistics people, research, and impact.
Alejandro Hernandez was a Computer Science student in his undergraduate studies, but found his way to studying biostatistics in graduate school due to a motivation and drive to apply data science in ways that improve people’s lives.
Biostatistics PhD student Yinxiang Wu has won a 2025 Distinguished Student Paper Award from the American Statistical Association Section on Statistics in Genomics and Genetics (SSGG) for his work, “A More Credible Approach to Multivariable Mendelian Randomization.”
Biostatistics student Miaolei Bao came to UW to understand the rationale and statistical rigor underlying scientific studies. In a new Q&A, she reflects on her experiences in the Master of Science Capstone program.
Review highlights of University of Washington Department of Biostatistics member accomplishments during 2024.
UW Biostatistics Doctoral Student Quinn White's research is part of a growing effort to assess the implications of including race and ethnicity in clinical risk prediction models. White is first author of a recent study which examined the use of race in the Multi-Ethnic Study of Atherosclerosis (MESA) algorithm used to calculate the 10-year risk of coronary heart disease. The score calculation not using race predicted heart disease as well as the original calculation that did.
A research team at the University of Washington (UW) has been approved for more than $1 million in research funding by the Patient-Centered Outcomes Research Institute (PCORI) to develop statistical methods for analysis of platform trials.
University of Washington Biostatistics staff member Maggie Tarnawa recently expanded her responsibilities as curriculum coordinator to include creating professional development programming for UW Biostatistics students. Learn more about the additional programs and resources Tarnawa has in the works for the upcoming year.
University of Washington researchers Sharon Browning and Seth Temple co-authored a study proposing new statistical methods for detecting signatures of strong natural selection that have occurred in humans in the past several thousand years.