Group Leader
Andrew R. Jamieson, Ph.D.
Andrew R. Jamieson, Ph.D., is an Assistant Professor in the Lyda Hill Department of Bioinformatics at UT Southwestern Medical Center, appointed in 2019. As Principal Investigator, Dr. Jamieson leads a team of scientists and machine learning engineers focused on developing advanced AI systems for analyzing medical student performance. His research leverages UTSW Simulation Center's vast catalog of live-action human performance data, including video, audio, and text-based inputs, to guide frontier multimodal foundation models towards expert-level automated assessment and educational enhancement. This innovative approach aims to provide educators with unprecedented insights into human behavior and communication in medical settings. In 2023, Dr. Jamieson's team achieved a significant milestone by developing and deploying a pioneering automatic AI grading system for medical student post-encounter OSCE notes.
From 2018 to 2021, Dr. Jamieson served as co-leader of the Bioinformatics Core Facility (BICF), spearheading campus-wide research collaborations in computational image analysis. Dr. Jamieson's work in machine learning and image analysis has been featured on the cover of Cell Systems (July 2021), where he developed a generative deep network to encode latent representations of live-imaged, label-free melanoma cells to reveal cellular properties distinguishing aggressive from less aggressive metastatic melanoma. In the domain of spatial biology, he has collaborated closely with pathologists and radiation oncologists to develop custom pipelines and visualization tools for analyzing highly-multiplexed immunofluorescence images. In response to the global pandemic, his team developed the UTSW COVID-19 forecast model, providing critical data to institutional leadership and the public. Dr. Jamieson is also an active educator contributing to various graduate-level courses and nanocourses, including as a Course Director for the Masters in Health Informatics program at the Clinical Informatics Center.
Prior to his academic career, Dr. Jamieson held key industry positions, including roles at GE Healthcare working in the molecular diagnostics and BioPharma space, and as the first data scientist at a big data analytics start-up. Dr. Jamieson 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 laid the foundation for a career-long fascination with machine learning and AI.
SimCenterAI Team
Mike Holcomb M.S. - Lead Data Scientist
Mike has a BS in Mechanical Engineering from Rice University and an MS in Computer Science from UT Dallas. After a decade of working in finance, Mike reoriented to Artificial Intelligence and Machine Learning and joined the Jamieson Lab in 2020. Shortly after starting at UTSW, Mike's work was immediately impactful having developed UTSW's Dallas-area COVID-19 forecasting model. Mike now works on designing and evaluating novel machine learning solutions across a wide variety of data domains and research endeavors.
Shinyoung Kang - Data Scientist
Shin graduated from Emory University and is focused on advanced vision models.
Dave Hein, MS - Data Scientist
Dave Hein received a B.S. in Chemistry and an M.S. in Data Science from the University of Texas at Austin. He started his career at UTSW as a research assistant in the radiation oncology department where he gained experience in clinical oncology research and bioinformatics. Now as a data scientist in the Jamieson lab, he innovates at the intersection of healthcare and AI, developing large language model pipelines for analyzing kidney cancer records and analysis workflows for spatial transcriptomics data.
Ameer Hamza Shakur, PhD - Data Scientist / ML Engineer
Ameer graduated with a Dual Degree from IIT Madras and a PhD in Industrial Engineering from the University of Washington, Seattle. His interests are centered around Machine Learning and Artificial Intelligence, particularly in the healthcare space, and he has experience developing machine learning solutions in a variety of domains. At UTSW, Ameer is working across the LLM stack to develop a first of its kind automatic assessment system for medical education.
Students & Interns!
Hunter Schuler, M.S. - PhD Student [SMU]
Hunter received a B.S. in Biology, a B.S. in Applied Mathematics, and an M.S. Mathematics from Texas State University. He is currently a Statistics PhD candidate at Southern Methodist University. Prior to joining the Jamieson lab, Hunter worked in a variety of environments including pharmaceutical, clinical, and research laboratories. At SMU, he has previously worked as a statistics consultant for academic clients and a teaching assistant instructing undergraduate statistics and data science courses. Hunter also previously served in the Army National Guard.
Antony Gitau - Masters Student - [AI For Science at the University of Cape Town]
Antony M. Gitau is a Google DeepMind Scholar studying a master's degree in Artificial Intelligence for Science at the University of Cape Town (UCT) and the African Institute for Mathematical Sciences (AIMS), South Africa.
He holds a B.Sc. in Biomedical Engineering degree from Kenyatta University, Nairobi, Kenya. As an undergraduate, Antony gained research experience in artificial intelligence, working in labs in Kenya and Uganda on computer vision and natural language processing projects. He has also received multiple scholarships to participate in or present his work at international data science events in countries such as Greece, France, Norway, Ghana, and Rwanda.
Antony’s core research interest lies in solving biomedical problems by developing or improving machine learning methods. At Jamieson Lab, he is studying the development and validation of frontier workflows based on multimodal foundation models for automated Objective Structured Clinical Examination (OSCE) assessments, focusing on near-real-time analysis of medical student–standardized patient interactions as part of his master’s thesis. Learn more about his journey at antony-gitau.github.io.
Aarash Zakeri - college student
Aarash is an undergraduate at the University of Pittsburgh studying Computational Biology. He is helping to create the UI and is excited to help the Jamieson Lab push forward in developing new technologies for medical professionals.
AJ Jain - PhD Student (UTSW)
AJ is a PhD student in Biomedical Engineering at the University of Texas Southwestern Medical Center, co-advised by Dr. Anila D’Mello and Dr. Milo Lin in Bioinformatics. He completed his B.A. in Neuroscience with minors in Computer Science and Statistics/ML at Princeton University. AJ works on applications of statistical computing, particularly network and graph-theoretic analysis, to brain imaging and behavioral data. He did his undergraduate thesis work on semantic network models of verbal fluency in children and is excited to continue investigating the intersection of language, cognition, and AI in a biomedical context while collaborating with the Jamieson group. In his spare time, AJ can be found watching shows, creating/listening to music, consuming boba, or laughing at memes.
Jake Lawson, M.S. (Cornell)
Jake is an undergraduate at Cornell University! Jake built custom language modeling interfaces for our SimCenterAI team.
Alumni
Henry Liu - College Student (Tufts)
Henry Liu is an undergraduate at Tufts University, majoring in Computer Science. He joined the Jamieson Lab via the U-Hack Med Gap year 2020 program. Henry works on automating surgical skill assessment via advanced video analysis.
Sol Vedovato, M.S. - Data Scientist
Sol Vedovato is a data scientist working on multimodal deep learning applications for complex medical data. Sol has an M.S. in Cognitive Science from Rensselaer Polytechnic Institute and has worked on Artificial Intelligence implementations for natural language processing, surgical videos, translation, and high-energy physics.
Zhiguo Shang, Ph.D. - 3D Computer Vision Specialist
Zhiguo Shang, Ph.D. is a Computational Scientist specializing in image analysis. He currently works on light sheet & CT medical images with diverse image analysis & machine learning tools, such as 2D/3D segmentation, skeletonization, and advanced pattern recognition techniques. He also works on developing algorithms & methods to address specific goals in 3D quantitative analysis.
Mengxi (Kate) Yu, MD. Ph.D. - Spatial Biology Computer Vision Scientist
Mengxi Yu, MD. Ph.D. is a Visiting Research Scholar. Prior to joining UTSW she was a postdoctoral scholar at the University of Chicago working on single-cell metabolics and cellular image analysis. Previously, Dr. Yu served as a medical doctor in China, specializing in Plastic Surgery. Currently, Dr. Yu is working to develop advanced machine learning approaches for clinically-oriented spatial biology applications on hyperplexed imaging platforms.