Our mission is to create methods to fit the science and not make science fit the methods.
Specifically, we are interested in the following questions that have clinical relevance:
We are also interested in the following frameworks that have computational relevance:
We form small teams comprising individuals with complementary expertise and work persistently to build comprehensive solutions. If you are interested in joining us, then we encourage you to contact an active lab member and talk about your interests.
We are grateful for funding from the American Heart Association, the National Heart, Lung, and Blood Institute, the National Cancer Institute, and the National Institute of Diabetes and Digestive and Kidney Diseases. We also thank the Karen Toffler Charitable Trust, Johnson & Johnson Enterprise Innovation Inc., and Visterra Inc., for funding our work.
New paper! Multimodal deep learning for dementia, published in Nature Communications.June 2022
Shangran Qiu defends his PhD and joins Microsoft Inc. as an Applied Scientist.May 2022
New paper! Graph-transformer for digital pathology, published in IEEE Transactions on Medical Imaging.May 2022
New award! Yi Zheng wins 2022 Department of Computer Science Research Excellence Award, awarded annually to a graduate student for their outstanding research.May 2022
New paper! Machine learning for pre-med trainees, published in Artificial Intelligence in Medicine.May 2022
Ray Jhun graduates with an MD degree and joins the neurology residency program at the University of North Carolina, Chapel Hill.January 2022
New paper! Spotlight on subtyping Alzheimer's disease, published in Trends in Molecular Medicine.January 2022
New grant! We received a pilot award from the Johnson & Johnson Enterprise Innovation, Inc.December 2021
Xiao Zhou defends his PhD in Computer Science and starts postdoctoral research at Yale University.