PNNL

Jen (Huckett) Willis joined PNNL in June 2020 as a data scientist. She holds a Ph.D. in statistics from Iowa State University and has 15 years of professional experience developing statistical methodology in numerous application domains, including national defense architecture development (Department of Homeland Security’s Countering Weapons of Mass Destruction), arms control and associated confidence modeling, stochastic modeling of medical mitigation and laboratory sample processing in response to terrorism events (Department of Homeland Security’s Terrorism Risk Assessment), quantifying energy savings resulting from rate-payer investments in utility energy efficiency programs for regulatory requirements, as well as informing future program design decisions (utilities and energy consortiums across the United States), and individual privacy and confidentiality protection (U.S. Census Bureau).  

As a member of PNNL’s National Security Directorate, Jen has been involved in the following main thrust areas: 

• Defense architecture development: developing chemical, radiological/nuclear, and biological defense architectures that represent the United States’ regulatory landscape and defense capabilities with respect to national level events. 
• Risk assessment and reduction applied to resource allocation: developing risk models incorporating threat, vulnerability, and consequence for ferry systems, airports, and airport check points that provide sponsors with asset allocations that minimize risk from vehicle and/or person-borne improvised explosive devices, various threat objects (weapons), and chemical or biological agents and explosives; considering passenger trust, screening operations, and current and future technology innovations.  
• Statistical based sampling and geospatial data analysis: review, recommend, and develop methods for subsurface survey design and geospatial analysis included in Visual Sample Plan (VSP); provide data quality objectives (DQO) guidance and processes that enable sponsors and stakeholders to adhere to government guidance (e.g., EPA G-4 and G-9) to identify data requirements for making defensible decisions in environmental assessments, ensuring systematic planning and statistically defensible sampling plans meet project objectives, and facilitating stakeholder engagement and transparency​. 
• Develop methodologies and models to infer system confidence from data collected through integrated monitoring and verification measures, applied as a component of nuclear arms control during inspections of a nuclear enterprise. 

• Dr. Willis has expertise in risk modeling, randomized control trial study design, statistical analysis and model development, stochastic modeling and simulation, and sample design for surveys and site visits. 
• She has experience in successful project management and technical leadership.  
• She has extensive experience programming with R statistical software. 

• Ph.D. and M.S., Statistics – Iowa State University
• B.S., Mathematics – New Mexico Institute of Mining and Technology

• American Statistics Association (ASA) member (2010–present)
• Northwest Strategic Energy Management Collaborative
  • Leadership Team (2019–2020)
  • Member (2017–2020)
• Northwest Power and Conservation Council Regional Technical Forum
  • Voting member (2016–2018)
  • Corresponding member (2019–2020)
• Lawrence Berkeley National Laboratory Measurement & Verification 2.0 Stakeholder Advisory Group member (2016–2018)