Robert Jeraj

University of Wisconsin School of Medicine and Public Health. 


Professor, Medical Physics and Human Oncology. Education: B.Sc., Physics, University of Ljubljana, Slovenia, Ph.D., Physics, University of Ljubljana, Slovenia. Research Interests: Tumor Heterogeneity and Treatment Resistance, Quantitative Imaging Biomarkers, Image Guidance for Precision Medicine, Modeling in Oncology and Neurology.

Professor in the Departments of Medical Physics, Human Oncology, Radiology and Biomedical Engineering at the University of Wisconsin-Madison. At the UW Carbone Cancer Center, I lead the Imaging and Radiation Sciences program. I also direct the UW Carbone Cancer Center Translational Imaging Research program that oversees concept development, protocol design and implementation in trials incorporating novel anti-cancer therapies with imaging endpoints. In addition, I direct the Wisconsin Oncology Network of Imaging eXcellence (WONIX), a network, which conducts trials with advanced imaging endpoints through the State of Wisconsin. I have a broad background in medical physics, with extensive research experience in the use of molecular imaging for treatment assessment and use of novel imaging in drug development. I am a member of numerous committee positions within the AAPM, APS, ECOG-ACRIN and several other organizations. I also serve as a member of the Board of Commission on Accreditation of Medical Physics Education Programs (CAMPEP), a member of the External Advisory Board of the Metrology for Medical Physics Centre of the National Physics Laboratory (NPL), UK, and a member of the International Advisory Board of the National Research Center for Radiotherapy (DCCC Radiotherapy), Denmark. I have an extensive track-record in cancer-related clinical research, particularly development of novel imaging biomarkers through advanced image analytics and their deployment in multiple local, national (e.g., ECOG-ACRIN) and international (e.g., ANZUP) clinical trials.


Artificial Intelligence in the Era of Precision Medicine

Ar<ficial Intelligence (AI) is quickly entering many aspects of our lives, including medicine. However, its role and impact is s<ll rela<vely uncertain. In this lecture, I’ll review poten<al and importance of AIsupported analy<cs and decision-making based on medical imaging, with specific focus on personalized oncologic therapies (precision medicine). I will review how the key stakeholders (medicine, imaging and business communi<es) perceive importance of AI in precision medicine. I will report on how AIsupported image analy<cs can help with treatment decisions, how it can uncover tremendous heterogeneity of treatment response and complex dynamics of individual cancer lesion response, which makes it difficult to op<mize cancer therapies. Finally, I will briefly review different methods for improving interpretability of AI tools, and regulatory frameworks for enabling adop<on of AI-supported tools in medicine.