Dr. Qin develops benchmark data, analytic methods, and computational tools to facilitate the reproducible statistical translation of high-dimensional biomedical data. In collaboration with wet-lab colleagues, she has orchestrated the design and collection of unique benchmark datasets, focusing on the important challenge of data harmonization for microarrays and sequencing. She has led the creation of novel simulation algorithms and software tools for unraveling the interplay between data harmonization and subsequent analyses, such as sample classification and survival prediction. She has also developed new statistical methodologies for promoting evidence-based practice of data harmonization. Her research program in reproducible statistical learning for cancer omics data has been supported by multiple completed and ongoing grants awarded by the National Institutes of Health (NIH).

Dr. Qin collaborates with a team of multidisciplinary investigators engaged in research on soft tissue sarcoma and colorectal cancer at MSK, contributing to the design and analysis of both retrospective and prospective studies. Notably, she serves as the Director of the Biostatistics and Bioinformatics Core for the MSK Soft Tissue Sarcoma SPORE (Specialized Program of Research Excellence). Over the years, Dr. Qin has also collaborated with researchers studying the molecular basis of various other cancer types, including breast, ovarian, pancreatic, and pediatric cancer.

Dr. Qin serves as a member of the Research Council at MSK, reviewing investigator-initiated and industry-sponsored protocols for scientific merit and priority. On a national level, she contributes her expertise as the Council of Sections Representative for the American Statistical Association’s Statistics in Genomics and Genetics Section and a Regular Member for the NIH’s ASPA Study Section.