A Computing, Inference and Learning lab at Penn School of Medicine

Dr. Yong Chen

Director of the Penn Computing, Inference and Learning (PennCIL) lab

Welcome From Yong Chen, PhD

“Improving human health by prime insights from data.”

In the last decade, there has been major advances in the production and collection of data, from medical research to patient wellness regimes. These vast new troves of data from electronic health records, claims/billing data, product/disease registries, genetic/genomic databases, medical devices and wearables offer a unique opportunity to make health care more proactive. Transforming these data into insights requires deep understanding of the provenance of the data, the collection procedure of the samples, the intercorrelations among the variables, the quality of the data, and the uncertainty associated with the analytical results from models.

Our overriding objective is to develop, apply and disseminate new methods and software for evidence generation using clinical trial and real-world data, and to bridge the gap from data to insights, and from insights to actionable health care.

For examples of our innovative research projects, please visit our xmeta-project as a comprehensive tool for advanced meta-analysis, and pda-project as an innovative solution for next generation data sharing for multi-institutional studies.

On behalf of our lab members, I want to thank the continuous funding supports from NIH, PCORI and AHRQ.



A comprehensive toolbox for advanced meta analysis.

PDA Methods

A solution for next-generation data sharing.