Andrew Jamieson, Ph.D. Titles and Appointments Assistant Professor School Medical School Department Lyda Hill Department of Bioinformatics Graduate Programs Biomedical Engineering Biography Andrew R. Jamieson, Ph.D., is an Assistant Professor in the Lyda Hill Department of Bioinformatics at UT Southwestern Medical Center. He leads a team of scientists and machine learning engineers developing advanced AI systems to solve both clinical and research problems—ranging from automated analysis of human performance and communication to decision support in complex biomedical workflows. His most recent work focuses on leveraging multimodal foundation models that integrate video, audio, and text to turn rich, real-world interactions into objective, scalable assessment and feedback. In collaboration with UT Southwestern’s Simulation Center, his group has pioneered automated evaluation of clinical encounters, including one of the first deployed AI systems for grading medical student post-encounter notes in OSCE-style assessments. From 2018 to 2021, Dr. Jamieson served as co-leader of the Bioinformatics Core Facility (BICF), where he drove campus-wide collaborations in machine learning, image analysis, and data engineering. His work has been featured on the cover of Cell Systems (July 2021), where he developed a generative deep network to learn latent representations of live-imaged, label-free melanoma cells and uncover features associated with metastatic behavior. He has also partnered with pathologists and radiation oncologists to build custom pipelines and visualization tools for highly multiplexed spatial biology and other complex imaging modalities. In response to the COVID-19 pandemic, Dr. Jamieson’s team developed the UTSW COVID-19 forecast model, providing critical operational insight to institutional leadership and the public. He is an active educator and program builder, contributing to graduate-level courses, nanocourses, and the Masters in Health Informatics program, with a particular emphasis on practical, safe, and responsible application of AI in real-world clinical and research workflows. Prior to his academic career, Dr. Jamieson held key roles in industry, including positions at GE Healthcare in molecular diagnostics and BioPharma, and as the first data scientist at a big data analytics start-up. He received his B.A. in Physics with honors (2006) and Ph.D. in Medical Physics (2012) from the University of Chicago, where his early work in computer-aided diagnosis of breast cancer laid the groundwork for a career at the intersection of AI, complex data, and medicine. Education Undergraduate University of Chicago (the) (2006), Physics Graduate School University of Chicago (the) (2012), Medical Physics Research Interest AI in medical education and the clinic Frontier Artificial Intelligence Large Langauge Models Multimodal Foundation Models for Clinical Applications Publications Featured Publications Iterative refinement and goal articulation to optimize large language models for clinical information extraction. Hein D, Christie A, Holcomb M, Xie B, Jain AJ, Vento J, Rakheja N, Shakur AH, Christley S, Cowell LG, Brugarolas J, Jamieson AR, Kapur P, NPJ Digit Med 2025 May 8 1 301 Rubrics to Prompts: Assessing Medical Student Post-Encounter Notes with AI Andrew R. Jamieson and Michael J. Holcomb and Thomas O. Dalton and Krystle K. Campbell and Sol Vedovato and Ameer Hamza Shakur and Shinyoung Kang and David Hein and Jack Lawson and Gaudenz Danuser and Daniel J. Scott NEJM AI 2024 1 12 Interpretable deep learning uncovers cellular properties in label-free live cell images that are predictive of highly metastatic melanoma. Zaritsky A, Jamieson AR, Welf ES, Nevarez A, Cillay J, Eskiocak U, Cantarel BL, Danuser G, Cell Syst 2021 May Universal consensus 3D segmentation of cells from 2D segmented stacks. Zhou FY, Marin Z, Yapp C, Zou Q, Nanes BA, Daetwyler S, Jamieson AR, Islam MT, Jenkins E, Gihana GM, Lin J, Borges HM, Chang BJ, Weems A, Morrison SJ, Sorger PK, Fiolka R, Dean KM, Danuser G, bioRxiv 2025 Mar Large Language Models for Medical OSCE Assessment: A Novel Approach to Transcript Analysis Ameer Hamza Shakur, Michael J. Holcomb, David Hein, Shinyoung Kang, Thomas O. Dalton, Krystle K. Campbell, Daniel J. Scott, Andrew R. Jamieson arXiv 2024 Zero-Shot Multimodal Question Answering for Assessment of Medical Student OSCE Physical Exam Videos Michael J. Holcomb, Shinyoung Kang, Ameer Shakur, Sol Vedovato, David Hein, Thomas O. Dalton, Krystle K. Campbell, Daniel J. Scott, Gaudenz Danuser, Andrew R. Jamieson medRxiv 2024 Heterozygous Mutation of Vegfr3 Reduces Renal Lymphatics Without Renal Dysfunction. Liu H, Hiremath C, Patterson Q, Vora S, Shang Z, Jamieson A, Fiolka R, Dean K, Dellinger M, Marciano D, J Am Soc Nephrol 2021 Sep Rethinking Autonomous Surgery: Focusing on Enhancement over Autonomy. Battaglia E, Boehm J, Zheng Y, Jamieson AR, Gahan J, Majewicz Fey A, Eur Urol Focus 2021 Jul A Silver Lining? Fewer non-SARS-CoV-2 Respiratory Viruses during the COVID-19 Pandemic. Most ZM, Holcomb M, Jamieson AR, Perl TM, J Infect Dis 2021 Apr What the Coronavirus Disease 2019 (COVID-19) Pandemic Has Reinforced: The Need for Accurate Data. Arvisais-Anhalt S, Lehmann CU, Park JY, Araj E, Holcomb M, Jamieson AR, McDonald S, Medford RJ, Perl TM, Toomay SM, Hughes AE, McPheeters ML, Basit M, Clin Infect Dis 2021 03 72 6 920-923 Results 1-10 of 15 1 2 Next Last
