Qi Long, PhD
Professor and Vice Chair of Faculty Professional Development
Department of Biostatistics, Epidemiology and Informatics
Associate Director for Quantitative Data Science, Abramson Cancer Center
Dr. Long’s research program bridges novel statistical and ML/AI research and impactful biomedical research. Its thrust is to develop robust statistical and ML/AI methods and models for advancing precision medicine and population health. Specifically, he has developed responsible statistical methods and ML/AI models for (integrative) analysis of big health data (such as -omics data, electronic health records data, and imaging data), missing data, causal inference, data privacy, algorithmic fairness, Bayesian methods and clinical trials. More recently, Dr. Long’s research has branched into LLMs, foundation models and AI agents for biomedicine. Dr. Long’s methodological research has been supported by the National Institutes of Health (NIH), the Patient-Centered Outcomes Research Institute (PCORI), the National Science Foundation (NSF), and the Advanced Research Projects Agency for Health (ARPA-H).
Dr. Long has directed the Statistical and Data Coordinating Center for national research networks and large-scale multi-site clinical studies – supervising a team of database administrators and programmers, application developers and statistical analysts. He currently co-directs (with Dr. Nicola Mason at Penn Vet) the Coordinating Center for the Premedical Cancer Immunotherapy Network for Canine Trials (PRECINCT), part of NCI’s Cancer Moonshot Initiative, and co-directs (with Dr. Jesse Hsu) the Statistical and Data Coordinating Center for the Risk Underlying Rural Areas Longitudinal (RURAL) Cohort Study, funded by NIH/NHLBI.
Dr. Long is the founding Director of the Center for Cancer Data Science, Associate Director for Cancer Informatics of the Penn Institute for Biomedical Informatics, and Associate Director for Quantitative Data Science of the Abramson Cancer Center at the University of Pennsylvania.
Dr. Long is an elected fellow of the American Association for the Advancement of Science (AAAS), the American Statistical Association (ASA), the Institute of Mathematical Statistics (IMS), and the International Statistical Institute (ISI).
Current Research
The Long Lab‘s mission is to advance responsible and trustworthy data science and AI for precision medicine.
Research areas: Robust statistical and machine learning methods for analysis of big, complex health data including -omics, electronic health records (EHRs), imaging data, and mobile health (mHealth) data; missing data; causal learning; data privacy; bias and fairness in AI for medicine; Bayesian methods; clinical trials