Justin Zhan develops algorithms to enhance computational speed and efficiency of applications requiring massive amounts of streaming data.
Credit: University of Arkansas
A $1.25 million grant from the Department of Defense will enable data science researcher Justin Zhan to develop novel algorithms to enhance the speed and efficiency of computational software that uses large amounts of streaming data.
By harnessing big data analytics faster and more efficiently, the algorithms will significantly enhance computational performance of many applications and programs that require massive amounts of streaming data. This so-called machine-learning approach to big data analytics will improve operational robustness, in addition computational speed and efficiency.
“Technological advances in this area have enabled the ability to ingest disparate data sets, program relevant conditions and rules, and derive insights and prescriptive intelligence in an unprecedented fashion,” said Zhan, who is a professor in the Department of Computer Science and Computer Engineering. “With these advances and with unprecedented access to high volumes of data, we can now empower data-driven architectures in near or real time.”
For example, tools such as hyperspectral imaging and functional magnetic resonance imaging have been hampered by an inability to handle large sets of dense data. Hyperspectral imaging collects and processes information from across the electromagnetic spectrum to find objects, identify materials and detect processes.
Likewise, to be able to measure brain activity by detecting changes associated with blood flow, functional magnetic resonance imaging demands computational ability to process massive quantities of streaming data. The inability to process large sets of data has compromised the performance of both tools, and Zhan expects his algorithms to enhance their performance dramatically.
Zhan’s research focuses on big data, blockchain technologies, information assurance, social computing and biomedical informatics. He has published more than 240 articles in peer-reviewed journals and conferences and delivered more than 30 keynote speeches and invited talks.
As a principal investigator or co-principal investigator, Zhan has been involved in more than 50 projects funded by the National Science Foundation, Department of Defense and the National Institutes of Health.
He is also a scholar with the Arkansas Research Alliance Academy.
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