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.
NSF: Predictable Wireless Networked Collaborative 3D Reconstruction for Real-Time Augmented Vision.
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.
MTTC: Virtual Histology with Volumetric Computerized Tomography.
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.