Dr. Jun Deng is a Professor at the Department of Therapeutic Radiology of Yale University School of Medicine and an ABR board certified medical physicist at Yale-New Haven Hospital. Dr. Deng obtained his PhD from University of Virginia in 1998 and finished his postdoctoral fellowship at Stanford University in 2001. Dr. Deng has been serving on the Editorial Board of numerous peer-reviewed journals, on the study sections of NIH, NSF, DOD, ACS, RSNA and ASTRO since 2005, and as scientific reviewer for various science foundations and institutions since 2015. Currently with funding from NIBIB, NSF, NCI, DOE and YCC, Dr. Deng’s research has been focused on artificial intelligence, machine learning, and big data for early cancer detection, real-time clinical decision support, digital twins of cancer patients, as well as AI-empowered mobile health and smart medicine.

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Dr. Deng’s research is primarily on two domains: artificial intelligence for precision medicine, and artificial intelligence for precision radiotherapy. In 2013 his group developed CT Gently, the world’s first iPhone App that can be used to estimate organ doses and associated cancer risks from CT and CBCT scans. In 2016 with a NIH R01 grant, Dr. Deng led the team to develop a personal organ dose archive (PODA), a big data approach to developing an early warning system to improve patient safety in radiation therapy. In 2019 funded by NSF, his team has been developing a generalizable data framework toward precision radiotherapy. Recently, Dr. Deng has joined a multi-institutional collaborative effort to develop digital twins for cancer patients, which has been funded by NCI in 2020 and DOE in 2021. In 2021, Dr. Deng has pioneered a new initiative towards individualized radiotherapy with patient engagement, an AI-empowered mobile health project funded by Yale Cancer Center.