Skip to Main Content U.S. Department of Energy
Website title


PNNL has a culture of assembling multi-disciplinary teams to solve the nation’s most complex problems. In analytics, we draw on a combination of disciplines from computer science, engineering, data sciences, applied mathematics, statistics, operations research, energy and environmental expertise, and fundamental sciences. There are more than 430 staff in our Computational and Statistical Analytics Division and Computational Sciences and Mathematics Division, and nearly 200 of these hold advanced degrees.

Applied Statistics and Computational Modeling

The Applied Statistics and Computational Modeling group is comprised of statistics, mathematics, and operations research experts who work in multi-disciplinary teams and employ powerful tools and techniques, such as mathematical modeling, optimization, statistical analysis, algorithm development, and operational modeling and simulation to solve complex problems and help clients reach mission-focused solutions.

This team develops optimal sampling and experimental designs to ensure the right type, quantity, and quality of data are gathered to support confident decisions and accurate conclusions while explicitly managing and quantifying uncertainty. Novel data-analysis methods are used to extract hidden features, anomalies, and signatures from high-dimensional, large-volume, multi-modal data in support of scientific discovery and quantifiable decision-making. Complex mathematical and stochastic models are developed to represent physical, chemical, biological, and nuclear phenomena, while experiments and sampling campaigns are used to increase confidence and explicitly manage and quantify uncertainty.

As leaders in applied statistics and mathematics research, this group's unique perspective provides practical solutions to important problems and generates data to influence policy decisions in industry and government.

Learn more

Cyber Technology and Analysis

Through our programs supporting the U.S. Department of Energy and the Strategic Partnership Projects (SPP) program, the Cyber Technology and Analysis group interacts with a myriad of government agencies including the U.S. Department of Defense, security, law enforcement, and intelligence communities. This group has taken a leadership role within the information operations field and is advancing the application of analytic methods, technologies, and sciences to meet ever-changing customer requirements. Multi-disciplinary teams are assembled to address cybersecurity, information assurance, information exploitation, information operations, and infrastructure protection challenges. Staff routinely:

  • perform analysis and provide timely technical assessments related to threats to computer systems
  • prototype processes to create/improve client analytic processes
  • actively support, grow, and conduct information infrastructure and cyber security programs.

Through these and many other efforts, this group focuses on providing expert delivery to national and homeland security challenges. The success in applying basic science to priority national programs (science to solutions) demonstrates that research and development initiatives are critical to addressing emerging customer requirements.

Learn more

Knowledge Discovery and Informatics

PNNL’s Knowledge Discovery and Informatics capabilities provide expertise in “knowledge-based information analytics,” the science of analytical reasoning facilitated by the tools and techniques of cognitive science, social and behavioral science, semantic systems, and human-information interaction.

Efforts range from cutting-edge research to fully deployed systems, including incorporation of complex legacy systems. As the management of knowledge is fundamental to the research process, PNNL’s capabilities span a wide array of technical disciplines and application areas. At the core of the work is the ability to identify, extract, represent, organize, synthesize, and retrieve knowledge.

Learn more

Risk and Decision Sciences

The Risk and Decision Sciences Group (R&DS) conducts research, development and support to help organizations make risk-informed decisions in uncertain and complex natural or engineered systems such as cyber security, environmental cleanup, nuclear safety and licensing and counter-terrorism. The R&DS team develops novel analytical methods and systems and integrates these methods with state-of-the-art technologies to help clients:

  • define their decision workspace
  • prioritize risks
  • develop defensible risk management strategies
  • identify, analyze and track spatiotemporal features and events
  • model and simulate events and state over space and time
  • design and implement decision-making tools

This team constructs robust software systems, applications and components that enable risk informed decision-making in existing and new software deployments through a system of systems (SoS) architectural approaches. PNNL's approach to modeling is built on robust, reusable software components that enable spatiotemporal analytics at scale from local to global extents on large databases.

Learn more

Secure Cyber Systems

Secure Cyber Systems works in partnership with government agencies and industry to perform research and development to deliver “first of a kind” solutions to protect our nation's critical strategic assets. Research at PNNL is addressing many of the big research questions facing our nation:

  • How can we predict the presence of potential vulnerabilities in complex infrastructures that are critical to energy and security missions or the potential for damage when adversaries gain new capabilities?
  • How can the broad energy infrastructure be made even more self-securing, so it can react fast enough to remain resilient under cyber attack without triggering negative, unintended consequences?
  • How can we ensure that data integrity and site security are maintained while supporting information availability, and that neither sensitive nor protected information is inadvertently leaked?

Current R&D efforts are focused in the following key areas:

  • large-scale situational awareness
  • cyber analytics: detection and discovery
  • critical infrastructure assessment and protection
  • information operations and systems exploitation
  • modeling and simulation of complex systems and networks.

Learn more

Software Engineering and Architectures

Our nation’s industrial and government infrastructure depends on complex software systems that range from sensor-based applications to large-scale, complex computer-based systems. PNNL uses a risk-based and “right sized” approach to provide a competitive advantage in the delivery of customized solutions involving complex information systems architectures that enable innovation in business processes, analysis systems, and scientific research.

Staff members have the knowledge and experience to design, develop, install, and operate complex software systems for applications that include sensor-based systems, integrated component systems, energy grids, manufacturing and business processes, and transportation and communication networks.

As the recognized leaders in the research, construction and deployment of software-centric complex operational systems, our expertise in combining adaptive architectures with solid engineering practices provides next generation research capabilities and cutting edge sustainable solutions to our clients across the entire product lifecycle.

Learn more

Visual Analytics

PNNL provides strategic value to our clients by discovering, developing, and deploying innovative visual analytics technologies that enable timely and profound insights from complex data. The goals are to stimulate analytical insight from massive, dynamic, ambiguous, and often conflicting information; to detect the expected and discover the unexpected; to provide timely and defensible assessments; and to communicate assessments effectively for action.

Key problems addressed by this group include:

  • enabling rapid analysis and discovery of insights from complex data that encompasses multiple dimensions, sources, data forms, time variants, languages and/or cultures
  • supporting application of human judgment to make the best possible use of incomplete, inconsistent, and potentially deceptive information in the face of rapidly changing situations.

Learn more

Computational Mathematics

This team leverages mathematical models to quantify and control scientific uncertainty to further scientific discovery. Scientific research and development is a process of gaining fundamental understanding of physical, chemical, and biological principles through computational modeling, experimentation, and data evaluation. As a leader in applied mathematics research, PNNL develops novel data-analysis methods to extract hidden features, anomalies, and signatures from high-dimensional, large-volume, multimedia data in support of discovery and confident decision-making. This group also develops methods and tools to optimize data-gathering approaches through sampling and experimental design.

Learn more

Data Sciences

The data sciences team possesses expertise in analytical reasoning, social and behavioral science, natural language processing, semantic technologies, and human-information interactions is fundamental to the analytics capabilities at PNNL. The core of this work is geared toward identifying, extracting, representing, organizing, and synthesizing data to create and manage knowledge. Knowledge management is fundamental to the research process, enabling staff and associated projects to span a wide array of technical disciplines and application areas.

Learn more

High Performance Computing

PNNL is employing high performance computing to solve scientific problems by developing and implementing high-level programming abstractions and high-speed networks and communication tools. Our approach merges science and technology by:

  • employing hardware that maximizes processor speed, memory and interconnect bandwidth, efficient use of secondary storage, and reliability
  • developing algorithms that are scalable, resource-efficient, and load-balanced and that manage computational complexity and exploit space-time locality
  • creating programming models, numerical libraries, communication libraries, compilers, and debuggers that support data decomposition, low communication overhead, and portability

The problem-solving environments that we provide also increase ease of use and availability of high-performance computing to non-specialists.

Learn more

Analytics at PNNL