• Ph.D. in Physics and M.S. in Robotics with 10 years of interdisciplinary research experience in biological physics, system biology, computational science, and microscopy. Integrated scientific disciplines to analyze complex systems and uncover their underlying mechanisms. • Proficient in developing advanced computational techniques for modeling and analyzing complex systems with expertise in machine learning, statistics, digital image processing, computer vision, spatial analysis, Monte Carlo simulation, (nonlinear) dynamical systems, PDEs, and parallel computing. • 8 years of experience processing and analyzing large-scale microscopy data across modalities including brightfield, multiphoton, light sheet, light field, and µCT. Experiences in stitching, denoising, segmentation, classification, registration (point cloud and volume), localization, and transformations, handling data from 1 to 5 dimensions. • 4 years of experience developing nonlinear optical systems, from conceptual CAD design and part fabrication to construction and calibration. Designed and implemented control software for multiday automated operations for 3D imaging of biological systems across scales. • Solid track record in project management within research and development settings, leading multi-institutional projects that involved collaborations among biologists, optical engineers, chemists, neuroscientists, and computer scientists. Demonstrated ability to secure funding through grant proposals, write scientific and engineering papers, and effectively communicate complex ideas across diverse fields.
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Postdoctoral ResearcherPrinceton UniversityUnited States -
Graduate Research AssistantUniversity Of California San Diego Jan 2017 - Dec 2023La Jolla, U.S.A.Whole mouse brain vascular network reconstruction and analysis. ▪ Developed efficient computational pipelines for descriptor-based 3D image stitching, 3D vascular image segmentation, skeletonization, learning-based graph proofreading. Converted 20 TB of raw images to a digitalized mouse brain vascular network embedded in a trillion-voxel 3D image space. ▪ Applied theory-driven topological and geometrical analyses to distill quantitative design rules of the vascular network.Automatic large-scale 3D imaging of heterogeneous biological tissue. ▪ Designed a serial two-photon microscope. Constructed the microscope using off-the-shelf and custom components. ▪ Developed control software for multi-day automatic operations and online data processing.
Xiang J. Education Details
Frequently Asked Questions about Xiang J.
What company does Xiang J. work for?
Xiang J. works for Princeton University
What is Xiang J.'s role at the current company?
Xiang J.'s current role is Postdoctoral Researcher.
What schools did Xiang J. attend?
Xiang J. attended University Of California, San Diego, Uc San Diego, Sun Yat-Sen University, The Affiliated High School Of South China Normal University.
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