Computational fluorescence microscopy
Prof. Qionghai Dai
Institute of Brain and Cognitive Sciences,
Date & Time
Thursday, 25 May 2023
Theatre C – Chow Yei Ching Building, HKU
Abstract: Long-term subcellular intravital 3D imaging in mammals is vital to study diverse intercellular behaviors and organelle functions during native physiological processes. However, optical heterogeneity, tissue opacity, and phototoxicity pose great challenges, leading to the tradeoff between the field of view, resolution, speed, and sample health. In this talk, I will discuss our recent work in multiscale intravital fluorescence microscopy based on computational imaging methods. Various large-scale fast subcellular processes are observed, including brain-wide neural recoding in mice at single resolution, 3D calcium propagations in cardiac cells, human cerebral organoids, and Drosophila larval neurons, membrane dynamics in zebrafish embryos, and large-scale cell migrations during immune response and tumor metastasis, enabling simultaneous in vivo studies of morphological and functional dynamics in 3D.
Biography:Qionghai Dai is a full Professor at Tsinghua University, the Academician of Chinese Academy of Engineering, Dean of the School of Information Science and Technology, and the director of the Institute of Brain and Cognitive Sciences at Tsinghua University. He is also the chairman of Chinese Association for Artificial Intelligence. Qionghai’s research centers on the interdisciplinary study of optics, informatics, neuroscience, and cognitive sciences, with hundreds of journal papers published in Nature, Cell, Nature Methods, Nature Biotechnology, etc. In the past decades, he has invented a series of mesoscale imaging systems and data analysis methods, facilitating simultaneous multi-scale observation of biological dynamics spanning from organelles, cells, tissue, and organs in different pathological or physiological states at a system level. His efforts open up a new horizon for the study of large-scale intercellular interactions, paving up the way from brain sciences to artificial intelligences. Recently, he is working on system neuroscience, artificial intelligence, computational imaging, large-scale data analysis methods, and neuromorphic optoelectronic devices.