Jing Hua - Research

 

 

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Research Areas

Research Topics

Research Projects

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Research Areas

    Computer Graphics and Visualization

-(Geometric processing and analysis, geometric modeling, physically-based modeling, scientific visualization)

    Image Analysis and Informatics

-(Geometric techniques for image analysis, learning and mining algorithms for imaging informatics, biomedical imaging applications, computational biomedicine)

   Computer Vision

-(reconstruction, feature extraction, shape analysis, tracking and motion analysis)

Research Topics

My recent research has focused on modeling, visualizing, exploring, analysis and assessment of digital representations of heterogeneous real world. The fundamental objectives of the advanced visual computing research are to unambiguously model high-dimensional heterogeneous data, automatically extract and retrieve their underlying information, interactively visualize their geometric, physical and other properties, accurately and effectively simulate their behaviors, and rigorously analyze their informatics and dynamic natures.

 

 3D Shape Diffusion, Abstraction, Matching and Registration
 Tracking and Analysis with Depth Images
 Reconstruction and Visualization of Motions from Noisy Point Sets
 Networked Sensing and Understanding
 Simplex Spline-based Volume Data Representation, Modeling, Reconstruction, and Visualization
 Geometric Representation, Analysis and Informatics for Data-Intensive Computing
 Visual Analytics in Large-scale Multimodality Imaging Data

 

Research Projects

NSF: Predictable Wireless Networked Collaborative 3D Reconstruction for Real-Time Augmented Vision.

NSF: Coordinated Visualization for Comparative Analysis of Cross-subject, Multi-measure, Multi-dimensional Imaging Data.

NSF: EAGER: Geometric Mapping and Diffusion for 3D Imaging Informatics.

NSF: III-CXT: Collaborative Research: Integrated Modeling and Learning of Multimodality Imaging Data across Subject for Brain Disorder Study.

NSF: CRI: IAD: Acquisition of Research Infrastructure for Knowledge-enhanced, Large-scale Learning of Multimodality Visual Data.

NIH: Longitudinal Neuroimaging in Sturge-Weber Syndrome.

NIH: Electrical, Molecular and Clinical Correlates of Human Interictal Spiking.

MTTC: Virtual Histology with Volumetric Computerized Tomography.

MTTC: Software Tool for Neuroimaging in Epilepsy.

21st Century Jobs Funds: HyperEye: Susceptibility Weighted Imaging-based Informatics Tools for Brain Tumor Studies.

 

Graduate students who are interested in the aforementioned research areas may contact Professor Jing Hua directly. Financial supports are available for qualified students.