Dr. Zhang is a board-certified clinical medical physicist, practicing in the Department of Radiation Oncology at University of Michigan. He joined the department in 2022. He received his PhD from the University of Colorado Boulder, followed by a medical physics research fellowship at Mayo Clinic Rochester and residency training at University of Pennsylvania.

Dr. Zhang's research focuses augmenting learning health system infrastructure via natural language processing. In particular, he is interested in workflow optimization, particularly through the implementation of advanced ClinOps analytics. He holds Epic certifications in Cogito, Caboodle Data Model, Clarity Data Model, and Access Data Model.

Dr. Zhang has published extensively and served on national committees within the American Association for Physicists in Medicine (AAPM). He has a keen interest in expanding the medical physics talent pipeline to foster growth and innovation.

Radiation oncology practices across the country utilize multiple information sytems to carry out clinical care. Typically, this involves a techical system, Radiation Oncology Information System (ROIS), that is tightly integrated with radiotherapy treatment devices, in addition to the hospital electronic health records (EHR) system. Thus, to answer clinical questions where technology may play an important role, it is necessary to consolidate and harmonize information from multiple, disparate information systems. To this end, I am interested in applying natural language processing methods to extract clinical information from EHR sources, and integrating it with treatment records hosted on the ROIS.