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mathematical sciences, Computational Sciences & Mathematics

PNNL’s Computing Research portfolio—spanning from basic to applied—includes data and computational engineering, high-performance computing, applied mathematics, semantic and human language technologies, machine learning, data and computing architectures, systems integration, and software and application development.
At PNNL, scientists, engineers, programmers, and researchers work together to apply advanced theories, methods, algorithms, models, evaluation tools and testbeds, and computational-based solutions address complex scientific challenges affecting energy, biological sciences, the environment, and national security.


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As the world continues to generate massive amounts of computerized data, visual analytics tools help make sense of it. User-Centered Evaluation of Visual Analytics, a new book by PNNL Chief Scientist Jean Scholtz, is helping researchers and developers by spotlighting best practices and trends in designing and evaluating visual analytics tools to make them as effective as possible for users.


Something New in the Air

Recently, PNNL added a new instrument to its roster of high-performance computing resources that aim to transform computer science research for both institutional users and external collaborators. Dubbed “BlueSky,” the reconfigurable experimental platform is capable of high-fidelity power and performance measurement and analysis of external devices with flexibility that sets it apart from other testbeds.

Power grid

Stressed Out: Can Models Predict Grid Tolerance to Environmental Extremes?

A research team led by PNNL scientists explored how well statistical models could predict grid stress based on weather conditions in a particular region. Scientists found a regression model provided predictive value and was easy to interpret.


Yeung Lands Prestigious Journal Entry

Congratulations to Enoch Yeung, a researcher with PNNL’s National Security Directorate, whose work exploring the role of feedback and interference in genetically engineered bacteria, “Biophysical Constraints Arising from Compositional Context in Synthetic Gene Networks,” was featured in the prestigious journal, Cell Systems.


Song Named IEEE Computer Society Early Career Honoree

Congratulations to Shuaiwen Leon Song, from PNNL’s HPC group, who was named a recipient of IEEE Computer Society’s 2017 Technical Consortium on High Performance Computing Award for Excellence for Early Career Researchers in High Performance Computing. Song will receive the award during this year’s International Conference for High Performance Computing, Networking, Storage and Analysis, known as SC17, in Denver.

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