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 cyber security. 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

Braden Soper: applied statistics, machine learning, mathematical modeling and simulation, game theory

Research Staff

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

Tal Ben Nun: high performance machine learning, programming languages, artificial intelligence for science, performance engineering, Scientific computing

Tom Benson: high performance computing, large-scale machine learning, performance analysis and optimization

Michael Brzustowicz: artificial intelligence, machine learning, data science

Nikoli Dryden: deep learning, systems for deep learning, communication libraries, I/O, HPC

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

Scott Kohn: cyber security, graph data management and analysis, HPC

Loic Pottier: performance modeling of HPC systems, scheduling, co-scheduling, scientific workflow optimizations, I/O performance

Claudio Santiago: integer programming, convex optimization, black box optimization

Tomas Valencia Zuluaga: optimization under uncertainty, decomposition methods, mixed-integer optimization, optimization of power systems planning, operation, and electricity markets

Jean-Paul Watson: optimization under uncertainty, scenario construction and analysis, mixed-integer programming, and critical infrastructure operations, planning, and resilience

William Yang: optimization under uncertainty, power systems, supply chains

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