TAMUQ Awarded QNRF Funding for 19 Projects

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  • Published: January 23, 2013
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TAMUQ Awarded QNRF Funding for 19 Projects

Publication Date:
June 29, 2017
A solar-powered desalination process, a polymer-enhanced foam to improve oil recovery in Qatari reservoirs and a wearable device to detect low blood sugar are just a few of the Texas A&M University at Qatar (TAMUQ) research projects selected to receive funding from the Qatar National Research Fund (QNRF).
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QNRF will fund 19 TAMUQ research projects in Cycle 10 of the National Priorities Research Program. TAMUQ’s research office was named Best Research Office of the Year for the third year in a row — and for the fifth time in the past six years.

“We are very pleased with the outcome of Cycle 10,” said Dr. César O. Malavé, dean of Texas A&M at Qatar. “Our researchers are working to address relevant, real-world challenges of relevance to the State of Qatar. Through this work, Texas A&M at Qatar directly contributes to Qatar’s goal of becoming a knowledge-based society. This latest round of awards from the Qatar National Research Fund demonstrates the high quality of the research being conducted at Texas A&M at Qatar, and we are grateful to QNRF for supporting our mission to be a valued resource to the State of Qatar as we work to support Qatar in achieving its goals.”

Many of the awarded projects feature collaborators from industry in Qatar and from other institutions around the world.
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Dr. Haitham Abu-Rub, chair of the Electrical and Computer Engineering Program, was awarded two projects this cycle, both with industry collaborators. The first project, co-funded by IBERDROLA QSTP, will focus on designing a smart dynamic control and management system for the existing power grid as an initial step in transforming it to a smart grid. Application of the work will be coordinated with the Qatar General Electricity & Water Corporation (KAHRAMAA). The second project, in collaboration with Siemens, will focus on developing and implementing a novel online fault management system to detect faults in the insulation of switchgears and cables in electric utility networks.

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