Publish Date: 10/02/2009

September has continued to be a very successful month for research awards! The Department is proud to announce that three new projects involving Computer Science faculty members have received funding through the National Science Foundation. The Department extends congratulations to Drs. Sandu, North, Ramakrishnan, and Quek on their new awards!

Dr. Adrian Sandu has received a National Science Foundation award for his proposal “General Linear Time-stepping Methods for Large Scale Simulations. “  

Dr. Sandu’s research will investigate theoretically order conditions for a class of general linear methods of practical importance. This theory will be used to develop new high order methods that circumvent the efficiency and accuracy reduction due to boundaries, sources, and stiffness. A rigorous analysis of the stiff behavior will be carried out in a singular perturbation framework, and will be extended to index one differential algebraic systems. The proposed research is the first to address strong stability preserving GL schemes for hyperbolic systems.

Dr. Chris North was recently awarded funding as a co-investigator with Drs. Lehman and House (Statistics Department) for their proposal “FODAVA: Bayesian Analysis in Visual Analytics (BAVA).” 

The goal of their research is to combine Visual Analytics and Bayesian Statistics. Currently, visualizations display inflexible deterministic transformations of data that inherently separate data visualization from visual synthesis. By changing the nature of the data transformation from deterministic to probabilistic Bayesian methods, manipulations to a display are possible to interpret quantitatively. The research immediately impacts how analysts discover new information in large datasets while the methodology will transition smoothly into the classroom. Students with varying backgrounds, interests, and talents, including undergraduates and underrepresented groups with limited academic history, will now have the opportunity to learn 21st century statistics.

Drs. Naren Ramakrishnan, Chris North, and Francis Quek have received funding through NSF for their “Formal Models, Algorithms, and Visualizations for Storytelling Analytics” proposal.  

The project focuses on the task of storytelling or the stringing together of seemingly unconnected pieces of data into a coherent thread or argument. The PIs will develop a new theory of relational redescriptions that will provide a uniform way to describe data and to compose data transformation algorithms across a multitude of domains. Using this theory, the PIs will be able to define stories formally as compositions of relational redescriptions. The team will develop scalable and steerable algorithms that will respond to dynamic user input and contextualize their use in interactive visualizations that harness the power of spatial layout. The researchers will also investigate how analysts engage in sense-making using the new storytelling algorithms and visualizations, in the hope of finding answers to questions such as: How do analysts achieve insight and advance their conceptualization of patterns derived from datasets?