معرفی
Giovanni Parmigiani is a Professor of Biostatistics at Harvard University, affiliated with the Dana-Farber Cancer Institute and the Harvard T.H. Chan School of Public Health. He serves as Associate Director for Population Sciences at the Dana-Farber/Harvard Cancer Center (DF/HCC) and directs the postdoctoral training grant in Quantitative Sciences for Cancer Research. Previously, he chaired the Department of Data Science at Dana-Farber (2009–2018) and led DF/HCC's Biostatistics and Computational Biology Program (2009–2015).
His research focuses on statistical methods for cancer data, including Bayesian modeling, machine learning for precision medicine, and genetic risk prediction. He develops tools like BayesMendel to assess cancer risk in families and PanelPRO for multi-gene risk modeling. Key areas include mutational signatures analysis, cross-study replicability in machine learning, and early cancer detection.
His work spans genomic data integration, clinical trial validation, and policy-relevant studies like vaccine effectiveness in cancer patients. He has contributed to guidelines for Lynch syndrome risk assessment and multi-cancer early detection programs like the PRECEDE study. Over three decades, he has mentored researchers in interdisciplinary teams, emphasizing data science as a bridge between fields.
