Bio
Dr. Jonathan Liu is a biomedical engineer and professor in the department of pathology, where his laboratory develops high-resolution optical-imaging devices and computational-analysis strategies for guiding treatment decisions. In particular, Dr. Liu's lab is developing non-destructive slide-free 3D pathology methods for clinical decision support and surgical guidance. In comparison to conventional slide-based pathology, 3D pathology provides: (1) vastly greater sampling of tissue specimens including whole biopsies and surgical margins, (2) volumetric imaging of cell distributions and 3D tissue structures that are prognostic and predictive, and (3) a non-destructive and reversible workflow that preserves valuable specimens for downstream molecular assays. The Liu lab works on a full stack of technologies to facilitate the clinical adoption of 3D pathology, from sample preparation (e.g. reversible optical clearing and fluorescence labeling), high-throughput imaging with open-top light-sheet (OTLS) microscopes developed within the lab, to data processing and AI-based image triage and analysis. For AI analyses, the lab develops both traditional machine classifiers based on intuitive “hand-crafted” 3D features, and deep-learning classifiers based on sub-visual 3D features. These non-destructive large-volume digital pathology methods are synergistic with the growing fields of radiomics and genomics, which collectively have the potential to improve treatment decisions for diverse patient populations. Dr. Liu received his B.S.E. degree at Princeton and his M.S. and Ph.D. degrees in mechanical engineering at Stanford. He was a postdoc and instructor within the Molecular Imaging Program at Stanford (MIPS) before transitioning to faculty positions at Stony Brook University (2010 – 2014) and the University of Washington in Seattle (2014 – 2025). Dr. Liu is a co-founder and board member of Alpenglow Biosciences Inc., which has commercialized the non-destructive 3D pathology technologies developed in his lab. Dr. Liu’s work is funded by the NCI, NIBIB, NIDDK, DoD, NSF, ARPA-H and various foundations.
