About Ngan Nguyen Ngan Nguyen Ph.D. Student, Computer Science computer graphics Scientific Visualization machine learning Ngan Nguyen is a Ph.D. candidate in the Computer Science Program under the supervision of Professor Ivan Viola in the Nanovisualization Research Group at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Education and Early Career Ngan has a Master's Degree in Computer Science. She worked at Gameloft Company as a Developer. After that, she joined the University of Information Technology, Vietnam National University in Ho Chi Minh City as a Lecturer. Research Interest Ngan is focusing on Computer Graphics, Visualization, and their overlaps into Articles Related News November 2020 Peering under the hood of SARS-CoV-Two 1 min read · Sun, Nov 8 2020 News visual computing Computer science COVID-19 Microscope and protein data are incorporated into an easy-to-use-and-update tool that can model an organism’s 3D appearance. May 2020 Modeling in the Time of COVID-19: Statistical and Rule-based Mesoscale Models 1 min read · Wed, May 6 2020 News visualization computer graphics bioinformatics We present a new technique for rapid modeling and construction of scientifically accurate mesoscale biological models. Resulting 3D models are based on few 2D microscopy scans and the latest knowledge about the biological entity represented as a set of geometric relationships. Our new technique is based on statistical and rule-based modeling approaches that are rapid to author, fast to construct, and easy to revise. From a few 2D microscopy scans, we learn statistical properties of various structural aspects, such as the outer membrane shape, spatial properties and distribution characteristics
Peering under the hood of SARS-CoV-Two 1 min read · Sun, Nov 8 2020 News visual computing Computer science COVID-19 Microscope and protein data are incorporated into an easy-to-use-and-update tool that can model an organism’s 3D appearance.
Modeling in the Time of COVID-19: Statistical and Rule-based Mesoscale Models 1 min read · Wed, May 6 2020 News visualization computer graphics bioinformatics We present a new technique for rapid modeling and construction of scientifically accurate mesoscale biological models. Resulting 3D models are based on few 2D microscopy scans and the latest knowledge about the biological entity represented as a set of geometric relationships. Our new technique is based on statistical and rule-based modeling approaches that are rapid to author, fast to construct, and easy to revise. From a few 2D microscopy scans, we learn statistical properties of various structural aspects, such as the outer membrane shape, spatial properties and distribution characteristics
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