“AI-based Solutions for Data Integration in Clinical Research”

Hosted by the Mallinckrodt Institute of Radiology (MIR)

Biography: Dr. José Marcio Luna obtained his M.S. in Electrical Engineering and Ph.D. in Engineering (with Ph.D. Minor in Applied Mathematics) from the University of New Mexico in 2010 and 2014 respectively. In 2021, Dr. Luna finalized his postdoctoral training at the Department of Radiology at the University of Pennsylvania, working with the Center for Biomedical Image Computing and Analytics (CBICA). His work at CBICA focused on the development and implementation of AI-based methods to predict treatment effectiveness in stage III non-small cell lung cancer patients receiving chemoradiotherapy. He also contributed with the theoretical development of interpretable machine learning methods for medical applications. During his postdoctoral training, Dr. Luna was the recipient of an Emerson Collective grant and was awarded the 2021 Marlene Shlomchik Fellowship by the Abramson Cancer Center. Dr. Luna recently joined Washington University School of Medicine as an Instructor of the Mallinckrodt Institute of Radiology. He has over 36 peer-reviewed research publications in high impact journals and premier conferences in engineering applications and medicine. His research program focuses on the development of translational tools for prediction and diagnosis of cancer from a multi-omics perspective in the era of precision medicine. Dr. Luna has a strong background in machine learning, data sciences, optimization theory and lung cancer research.

For inquiries contact Margaret Morton.