Leveraging IDIES Seed Funding support, a team led by Professor Tamer Zaki of the Department of Mechanical Engineering has received funding from the National Science Foundation for A Big Data Computational Laboratory for the Optimization of Olfactory Search Algorithms in Turbulent Environments.
Professor Zaki will use the unique Johns Hopkins Turbulence Databases to predict the source of contaminant release in turbulent environments. With researchers at the University of Tokyo the team will develop new olfactory search algorithms that use sensors to identify sources of pollutants and other agents released in the air or sea. Their work will use the Open Numerical Turbulence Laboratory’s virtual sensors and forward- and backward-particle tracking capabilities.
The proposal was submitted under IDIES to a joint US-Japan (NSF-Japan Science and Technology Agency) program on use of Big Data for disaster mitigation. It was one of six awarded grants ($300K, 01/04/15—31/03/18) featured in NSF press release 15-029.
For more information, please contact Tamer Zaki.