Yan Ma began his journey with Pitt Biostatistics in 2022, following stints as a professor and vice chair at the Department of Biostatistics and Bioinformatics at George Washington University Milken Institute of Public Health (2014-2022), and as an assistant professor at Hospital for Special Surgery and Weill Cornell Medical College (2008-2014).
Specializing in statistics, Ma has offered a diverse array of both conventional and innovative statistical consulting services to researchers in biomedicine and public health. His expertise has fostered successful collaborations, spanning traditional statistical domains like missing data imputation and machine learning to newer frontiers such as causal inference and meta-analysis. His work is marked by its focus on team science, translational science, and comparative effectiveness research, with applications in various fields including orthopedics, HIV/AIDS, and psychiatry.
Ma's contributions extend beyond the field of statistics to academia, where he has authored over 100 peer-reviewed publications. His work encompasses statistical methodology alongside biomedical and health services research, published in esteemed journals like Biometrics, JAMA, and Health Services Research. Notably, Ma has secured R01 grants from AHRQ and NIH, facilitating advancements in statistical methodologies for health disparities research.
His dedication to the field is prominent in his editorial roles for journals like The American Statistician and Statistical Analysis and Data Mining, and his service on review panels for NIH, PCORI, and the US Department of Veterans Affairs. Recognized for his contributions, Ma has received accolades including the Statistics in Epidemiology Young Investigator Award and the esteemed Team Science Award, acknowledging his role in translating research into clinical practice.
In 2017, Ma furthered his impact through a research fellowship with the Oak Ridge Institute for Science and Education at the U.S. Food and Drug Administration, and in 2022, he was honored with the Achievement in Academia Award from the Applied Public Health Statistics Section of the American Public Health Association, affirming his outstanding contributions to statistics and public health.