Dr. Wenjing Lou (CS) (http://www.cnsr.ictas.vt.edu/WJLou.htmland) and  Dr. Tom Hou (ECE) were awarded two new multi-institutional NSF research grants. The first, is entitled NSF CPS: Synergy: Collaborative Research: Cognitive Green Building: A Holistic Cyber-Physical Analytic Paradigm for Energy Sustainability. It aims to develop a unified analytical approach for green building design that comprehensively manages energy sustainability by taking into account the complex interactions between these systems of systems, providing a high degree of security, agility and robust to extreme events. This is a collaborative project between Profs. Ness Shroff and Qian Chen from Ohio State University, and Profs. Tom Hou (PI) and Wenjing Lou, from Virginia Tech.
The second award is entitled NSF CNS Collaborative Research: A Multi-Layer Approach Towards Reliable Cognitive Radio Networks.  The objective behind this project’s research activities is to develop technological solutions that ensure that cognitive radios operate in a trustworthy manner, in spite of potential security threats. It is a collaborative project between Profs. Wenjing Lou (PI) and Tom Hou from VT, and Profs. Wade Trappe and Yanyong Zhang from Rutgers University; with VT being the lead institution for this project.

 

CS@VT Affiliate Professor Nicholas Polys (http://cs.vt.edu/user/polys) and colleagues Drs. Michael Buehrer, Vuk Marojevic, and YalingYang, from ECE, received funding from the NSF DUE/IUSE program, for their proposal entitled Wireless Communication Test beds for Authentic STEM Learning.

 

 

 

Dr. Kirk Cameron (http://cs.vt.edu/user/cameron) and colleagues from the University of Houston, received NSF SHF funding for the proposal entitled Application-aware Energy Modeling and Power Management for Parallel and High Performance Computing.

 

 

 

 

 

Drs. Chris North (PI) (http://cs.vt.edu/user/north) and Yong Cao (http://cs.vt.edu/user/yongcao), and Department of Statistics Drs. Leanna House and Scotland Leman, received an NSF Big Data Award, entitled BIGDATA: F: DKA: Usable Big Data Analytics via Multi-Scale Visual to Parametric Interaction (MV2PI). Dr. North describes the research funded: “Gaining big insight from big data requires big analytics, which poses big usability problems.  In this proposal, human-computer-interaction research is merged with complex statistical methods and fast computation to make big data analytics usable and accessible to professional and student users. Multi-scale Visual-to-Parametric Interaction (MV2PI) enables analysts to simultaneously steer multiple algorithmic models across a continuum of data scales, from large data clouds to small working sets, by interacting directly with visualized data to adjust complex model parameters.”

 

Dr. Cliff Shaffer (http://cs.vt.edu/user/shaffer) and colleagues Dr. Susan Roger of Duke University and Dr. Tom Naps of University of Wisconsin-Oshcosh, received NSF IUSE funding. Dr. Shaffer is the PI for the VT-centered research on this grant. Dr. Shaffer says that the project “will study the efficacy of and disseminate a STEM learning environment named OpenDSA. OpenDSA is an open-source project with international collaboration. It has the potential to fundamentally change instruction in courses on Data Structures and Algorithms (DSA) and Formal Languages and Automata (FLA). ”

 

 

 

 

Dr. Chris North (http://cs.vt.edu/user/north) and Dr. Naren Ramakrishnan (http://cs.vt.edu/user/ramakrishnan) received funding from L-3 Communications for their proposal entitled: Discovering Coordinated Malicious Activity and Network Usage Patterns.  Quoting Dr. North: “In this project, we propose a visual analytics approach to cyber security network defense. We will adapt biclustering algorithms to detect coordinated malicious activities, and a method of chaining biclusters to uncover network usage patterns across large-scale cyber security datasets (e.g., network logs) by fusing multiple data domains.  We will create visualizations that enable human interaction with these algorithms and results to form characterizations of malicious behaviors.”

 

 

 

Drs. Wu Feng (http://cs.vt.edu/user/feng) and Eli Tilevich (http://cs.vt.edu/user/tilevich) received CRA-W funding for their proposal entitled Parallel Computing for Everyone. This funding is available to CS faculty to encourage female CS students to pursue research opportunities as part of their studies.  The researchers state that “This grant seeks to introduce explicit parallel computing abstractions into an educational programming language that is based on MIT’s Scratch visual programming langauge. This omission of explicit programming constructs is hard to rationalize given the ubiquity of multi- and many-core architectures. Enhancing Scratch with such parallel programming abstractions presents an unprecedented research and educational opportunity to mold the minds of the next generation of computer scientists to realize solutions that explicitly take advantage of parallel computing. Such abstractions (or components in Scratch terminology) include consumer-producer, pipes and filters, and process pool, just to name a few. These components will be realized to follow the Scratch design paradigm, where a component can be dragged onto the canvas and parameterized with the required values. The shape of a component determines to which other components it can be connected, thus providing the constraints whose satisfaction ensures that the resulting combination is semantically correct.”

 

Drs. Dennis Kafura (http://cs.vt.edu/user/kafura), Cliff Shaffer (http://cs.vt.edu/user/shaffer) , and Eli Tilevich (http://cs.vt.edu/user/tilevich) received NSF TUES EAGER funding for their proposal entitled: Scaffolding Big Data for Authentic Learning of Computing. In the word of Dr. Kafura the goal of this research is “to create curriculum and technologies that leverage Big Data with the proper scaffolding required to accommodate students with little or no programming background.”

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