Rate My Professor Tian-Ming Fu

Tian-Ming Fu is Assistant Professor of Electrical and Computer Engineering and the Omenn-Darling Bioengineering Institute at Princeton University, and is associated with the Princeton Neuroscience Institute. He received a B.S. in math and physics from Tsinghua University in 2011 and a Ph.D. in chemistry from Harvard University in 2017, followed by postdoctoral training at HHMI Janelia. Fu develops bioimaging, bioelectronics, and computational tools to quantitatively understand living organisms from molecular to multicellular scales. His laboratory creates novel optical microscopy methods, including super-resolution, light sheet, and adaptive optics techniques, along with bioelectronics devices such as nanoelectronics, flexible electronics, and photonics for high-resolution, minimally invasive multimodal imaging and manipulation. These approaches enable studies of molecular and subcellular dynamics in spatially compartmentalized and temporally dynamic multicellular organisms, with applications in cell and developmental biology, neuroscience, and tissue-device interfaces. During his graduate work, Fu contributed to the development of syringe-injectable mesh electronics for long-term brain electrophysiology. In his postdoctoral research, he advanced the MOSAIC multimodal optical scope with adaptive imaging correction for 4D high-resolution imaging of subcellular dynamics inside multicellular organisms. Fu received the NIH Trailblazer Award. His contributions have been recognized with honors including the Top 10 World Changing Ideas by Scientific American in 2015, Most Notable Research Advances by Chemical & Engineering News in 2015, the Material Research Society Graduate Student Award in 2015, and Top Technical Advances by The Scientist in 2018. Selected publications include “Cellular bases of olfactory circuit assembly revealed by systematic time-lapse imaging” in Cell (2021), “A method for single-neuron chronic recording from the retina in awake mice” in Science (2018), “Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology” in Proceedings of the National Academy of Sciences (2017), “Stable long-term chronic brain mapping at the single neuron level” in Nature Methods (2016), and “Syringe-injectable electronics” in Nature Nanotechnology (2015).