I am currently leading a Brain Big Data research group at the Allen Institute for Brain Science, Seattle, with the goal to develop revolutionary technologies to generate, manage, visualize, analyze, and understand massive-scale structure and function data related to brains, especially human brains. I am also an affiliate/adjunct faculty member (professor) with the University of Washington (USA) and the University of Georgia (USA), etc. Prior to my arrival at Seattle in the fall of 2012, I led a Big Image Mining research group at Janelia Research Campus, Howard Hughes Medical Institute, where I stayed for almost 7 years. Before then, I did research at a series of other interesting places, including for instance the Lawrence Berkeley National Laboratory, Johns Hopkins University Medical School, etc.
We develop and use many cutting-edge machine learning, artificial intelligence, data mining, and imaging methods to handle the very complex and very large scale brain data, gene expression data, and many other types of data. We welcome collaborations especially the large scale data challenges. Our group has been a world-leader in massive scale multi-dimensional imaging and visualization, very large scale brain mapping, neuron- and cell-phenotyping, feature extraction and Bayesian inferencing for general applications, as demonstrated in a number of high-profile, well-recognized publications and widely-used open-source software packages.
July, 2014: The Virtual Finger paper is published in Nature Communications. Virtual Finger lets you instantly get the 3D location of image objects as long as you can see [part] of it!
Jan, 2014: The Vaa3D system was featured in Nature Protocols. This long protocol paper explains 10 often used pipelines/procedures for visualizing and analyzing 3D+ biological images of a number of model systems.