Jing Qian

Dr. Jing Qian, Ph.D., is a medical physicist in the Department of Radiation Oncology at Mayo Clinic Comprehensive Cancer Center in Rochester, Minnesota. He holds an appointment at Mayo Clinic College of Medicine and is board-certified in Therapeutic Medical Physics by the American Board of Radiology. His clinical expertise focuses on proton therapy and improving radiation treatment delivery efficiency, outcomes, and safety.

Dr. Qian completed his Doctor of Philosophy in Physics at Yale University in 2009 and finished his residency in Radiation Oncology Medical Physics at Mayo Clinic in 2021. His early academic achievements include Yale University's Henry Fan Family Fellowship and Leigh Page Prize in 2002.

His research spans proton therapy optimization, quantitative image analysis, and artificial intelligence applications in radiation oncology. Recent work demonstrates his shift toward developing deep learning models for proton dose calculation, analyzing imaging signatures for treatment response prediction, and optimizing treatment delivery systems. His interdisciplinary approach bridges physics, oncology, and computer science to improve cancer treatment outcomes.

Dr. Qian's publication record shows consistent output in high-impact journals with an increasing focus on AI-driven solutions for radiation therapy challenges. His collaborative work spans multiple institutions and clinical specialties, reflecting the interdisciplinary nature of modern medical physics research.

• 2024 Distinguished Physics Researcher, Mayo Clinic Department of Radiation Oncology
• 2022 Mayo Scholar, Google Visiting Scholar
• Multiple beOUTSTANDING awards from Schlumberger Corporation (2014-2017)
• Outstanding Contributor and Most Valued Reviewer for Radiation Measurements journal
• Yale University's Henry Fan Family Fellowship and Leigh Page Prize (2002)

Dr. Qian actively mentors physics residents and postdoctoral fellows, contributing to the next generation of medical physicists. His work with Mayo Clinic's Comprehensive Cancer Center provides access to advanced proton therapy facilities and cutting-edge research infrastructure. His collaborations extend to Google researchers and multiple clinical departments within Mayo Clinic, creating a rich environment for translational medical physics research.

His laboratory work focuses on developing and validating new technologies for radiation treatment delivery and outcome prediction. Current projects involve AI-driven optimization of proton therapy systems, radiomics analysis of treatment response, and improving the precision of radiation dose delivery while minimizing toxicity.