The members of the Informatics Group perform research and development in the broad area of information management and analysis. Research topics include the development of new algorithms in bioinformatics, data management for large-scale attributed graphs, reconfigurable hardware acceleration for data-intensive computing applications, novel approaches for analyzing large collections of text, analysis and understanding of dynamic networks, streaming algorithms, and cybersecurity. Many of our problems involve very large data sets, such as text collections of tens of millions of documents, graphs with billions of edges, or streaming cyber data at hardware line speeds. We typically employ a variety of technologies and tools, such as machine learning and classification algorithms found in packages like WEKA, hardware such as the Tilera multicore engine, streaming middleware such as IBM’s Infosphere Streams, and open-source tools such as Hadoop and SOLR.

The customers of the Informatics Group include scientists and analysts both at the Laboratory and in the US Government. Many of our members work with our Global Security Directorate, and we receive external funding from the DOE Office of Science, DARPA, and various other U.S. Government agencies.

Group Lead

Brian Van Essen: spatial accelerators for embedded systems and HPC, reconfigurable computing, and memory architectures for data-intensive computing

Research Staff

Peter Barnes: parallel discrete event simulation tools and applications, communication networks

Tom Benson

David Buttler: database technology, web data access, web service selection, web document change detection

Brian Gunney: adaptive mesh refinement, HPC, numerical methods for partial differential equations, computational physics

David Hysom: combinatoric and discrete algorithms, scalable parallel methods, bioinformatics

Keita Iwabuchi: large-scale graph processing, out-of-core processing, HPC

Sam Ade Jacobs: parallel computing, large-scale graph (data) analytics, machine (deep) learning, and robotics

Chandrika Kamath: data mining, machine learning, signal and image processing, HPC

Scott Kohn: cybersecurity, graph data management and analysis, HPC

Celeste Matarazzo: cybersecurity, distributed agents, distributed sensor analysis

Roger Pearce: distributed file systems and tools to profile the I/O performance of data intensive applications

Tahsin Reza

Steve Smith

Michael Wyatt

Jae-Seung Yeom: data-dependent application behavior modeling, performance analysis, epidemic, viral evolution simulations

Andy Yoo: scalable large graph algorithms, large-scale data management, data mining and knowledge discovery, high-performance parallel computing, parallel algorithms