His research interests focus on the development, application, and benchmarking of advanced computational algorithms in medical imaging, with the intention of improving disease assessment, quantification, and diagnosis in the current clinical practice. He has been leading projects on image quantification, radiogenomics, and federated learning, towards enabling treatment selection models customized on an individual patient basis, while addressing health disparities and inequities.

Dr. Bakas has received grant funding from the National Cancer Institute of the National Institutes of Health, the National Science Foundation, the Abramson Cancer Center, and the Translational Biomedical Imaging Center of the Institute for Translational Medicine and Therapeutics of UPenn. He has co-authored >100 peer-reviewed manuscripts and >70 medical conference abstracts, with collaborators that span across academic ranks and disciplines. He is a founding board member of the MICCAI Society's Special Interest Group on Biomedical Image Analysis Challenges (SIG-BIAS), the Vice Chair for Benchmarking & Clinical Translation in the MLCommons’ Medical group, the co-lead of the AI-RANO working group, and has served as the organizer and chair of numerous challenges, workshops, and tutorials at both technical and clinical scientific meetings.