Efficient algorithms for processing and mining large datasets
University of Florida, Gainesville
Thursday, May 10, 2007
Talk: 10:45 am - 11:45 am
Host: Matt Mutka
A number of scientific and medical applications require processing, transmitting and mining of large and complex data sets. Our research has been focused on developing algorithms and software for such applications.
In this talk, we will briefly describe our work on the following applications:
- Mining metabolic networks for drug discovery: The human body at its genetic core consists of enzymes that catalyze reactions. These reactions generate compounds by consuming other compounds. Metabolic networks define the relationships between enzymes, compounds and reactions. We will describe novel computational methods for using metabolic networks in identification of target enzymes. Identification of these enzymes can accelerate the preclinical phase of the drug discovery process.
- Grid Resource Scheduling: Many grid based E-Science applications require transfer of large files. We will describe our work on scheduling bulk file transfers, where each transfer has a start time and an end time. We have formulated the problem as a special type of multi-commodity flow problem and have developed algorithms using this formulation. Simulation results show that these algorithms improve throughput and reduce rejection rate during admission control.
If time permits, we will also present our work on algorithms for feature detection and change detection in health care data.
Sanjay Ranka is a Professor in the Department of Computer Science. His current research interests are data mining, informatics and grid computing for data intensive applications in High Energy Physics, BioTerrorism and BioMedical Computing. Most recently he was the Chief Technology Officer at Paramark where he developed real-time optimization software for optimizing marketing campaigns. Sanjay has also held positions as a tenured faculty positions at Syracuse University and as a researcher/visitor at IBM T.J. Watson Research Labs and Hitachi America Limited.
Sanjay earned his Ph.D. (Computer Science) from the University of Minnesota in 1988 and a B. Tech. in Computer Science from IIT, Kanpur, India in 1985. He has coauthored two books: Elements of Neural Networks (MIT Press) and Hypercube Algorithms (Springer Verlag), 50+ journal articles and 80+ refereed conference articles. He serves on the editorial board of the Journal of Parallel and Distributed Computing and was a past member of the Parallel Compiler Runtime Consortium and the Message Passing Initiative Standards Committee. He was one of the main architects of the Syracuse Fortran 90D/HPF compiler. He is a fellow of the IEEE and AAAS, advisory board member of IEEE Technical Committee on Parallel Processing and a member of IFIP Committee on System Modeling and Optimization.