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Research asisstantship positions at this moment are available for the following three grants:
To apply, candidates are encouraged to submit the following to Dr. Milos Manic: 1. the resume, 2. papers that describes you the best (either published or your best work done for courses taken), 3. academic transcript.
Battlespace Awareness Through Critical Information Interdependency Visual Integration Tool (CIIVIT)
- Grant description:
- Dr. Milos Manic has received an $80,000 grant from the Department of Air Force. This grant was awarded as a result of a joint proposal with Idaho National Laboratory (INL). The objective of this grant is to provide a flexible and adaptable framework called the Critical Information and Interdependency Visual Integration Tool (CIIVIT) that will allow battle commanders to rapidly integrate the various dimensions of warfare into a highly visual and adaptable modeling environment. This framework will build upon an infrastructure interdependency model developed at INL called Critical Infrastructure Modeling System (CIMS©).
As a part of this grant, the University of Idaho (U of I) and INL teams will develop, as proof of principle, an add-on module to support decision makers in the multiple criteria analysis. This analysis will address tasks of Multiple Criteria Multiple Alternatives algorithms (MCMA) with enhancements using fuzzy logic and artificial neural networks.
- Specializations
- Candidates should have a specialization in computational technologies (neural networks and fuzzy logic) and decision support systems. Programming skills in Matlab are preferable.
A Fuzzy Approach for Bluetooth Intrusion Detection on Mobile Devices
- Grant description:
- Dr. Milos Manic has received a $75,000 grant from the Idaho National Laboratory. This grant was awarded as a result of a proposal with Idaho National Laboratory (INL). The objective of this grant is to provide work towards intrusion detections systems (IDSs) for Bluetooth technology on mobile devices. Many quantitative features involved in intrusion detection and security are associated with uncertainties i.e. fuzziness. Computational technologies can easily capture ambiguities.
Using this approach, the University of Idaho (U of I) and INL teams will integrate, as proof of principle, fuzzy frequent episode rules and fuzzy association rules to produce more flexible and abstract patterns for near real-time intrusion detection and prevention. Machine learning and data mining methods will be used to extract patterns automatically and adaptively from real-time data.
- Specializations
- Candidates should have specialization in intrusion detection systems and computational technologies. Programming skills in Matlab are preferable.
IDAHO EPSCoR RII: Idaho Experimental Watershed Network
- Grant description:
- Dr. Milos Manic has received a $75,000 grant from the IDAHO EPSCoR. The objective of this RII award is to enable the flexible and transparent cyber-infrastructure to assimilate, synthesize, restore and retrieve information into a coherent strategy. The purpose is to design the infrastructure for the foundation and implementation of various functionalities ranging from online complex database use to advanced web technologies related to communication, polling tools, web cast and other applications.
- Specializations
- Candidates should have specialization in GIS and advanced web technologies. Programming skills in client side languages are preferable.
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