Title: Data Mining for Bigdata Spatiotemporal Applications

Speaker: Sanjay Ranka, University of Florida, Gainesville

Abstract: Data collected for a number of applications from applications in science, engineering, medicine and business are spatiotemporal in nature. Spatial and temporal relations are implicitly defined and have to be extracted from datasets at the variable levels of granularity.Many of these applications require processing of datasets that have large volume (gigabytes to terabytes) and large velocity (substantial fractional of new data is added at regular intervals). Additionally, these applications have potentially multiple modalities of data with different levels of accuracy.

In this talk, we will present our recent work on data mining, machine learning and parallel processing of bigdata applications from CRM, remote sensing, health care and mobile computing. We will describe both the software infrastructure and algorithms required for end to end solution for these applications.

Bio: Sanjay Ranka is a Professor in the Department of Computer Information Science and Engineering at University of Florida. His current research interests are focused on a variety of issues related to data science: energy efficient computing, high performance computing, data mining and informatics. He is also interested in applying these techniques to applications in e-commerce, biology, medicine and engineering. 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 and a B. Tech. in Computer Science from IIT, Kanpur, India. He has coauthored two books: Elements of Neural Networks (MIT Press) and Hypercube Algorithms (Springer Verlag), 225 journal and refereed conference articles. His recent work has received a best paper award at BICOB 2014, best student paper award at ACM-BCB 2010, best paper runner up award at KDD-2009, a nomination for the Robbins Prize for the best paper in journal of Physics in Medicine and Biology for 2008, and a best paper award at ICN 2007. His research has been supported by NSF, NIH, Army, DOE, Samsung, Intel and Nvidia.

He is a fellow of the IEEE and AAAS. He is the associate Editor-in-Chief of the Journal of Parallel and Distributed Computing and an associate editor for ACM/IEEE Transactions on Computational Biology and Bioinformatics, IEEE Transactions on Parallel and Distributed Computing, IEEE Transactions on Computers, Sustainable Computing: Systems and Informatics, Knowledge and Information Systems, and International Journal of Computing. He was a past member of the IFIP Committee on System Modeling and Optimization, Parallel Compiler Runtime Consortium, the Message Passing Initiative Standards Committee and Technical Committee on Parallel Processing. He is the program chair for 2015 High Performance Computing, 2013 International Parallel and Distributed Processing Symposium, 2010 International Conference on Contemporary Computing and co-general chair for 2009 International Conference on Data Mining and 2010 International Conference on Green Computing.