Filtered by Computing & Analytics, Environmental Monitoring for Marine Energy, Hydropower, Testing for Marine Energy, Waste Processing, and Weapons of Mass Effect
Cyber, physical, and blended cyber-physical threats are real, ubiquitous, and expensive to deal with. Private companies, government institutions, and critical infrastructures struggle to implement viable solutions as technology evolves.
The Interfacial Dynamics in Radioactive Environments and Materials (IDREAM) Energy Frontier Research Center (EFRC) conducts fundamental science to support innovations in retrieving and processing high-level radioactive waste.
PNNL is heavily engaged in the development and use of mass spectrometry technology across its science, energy, and security missions, from fundamental research through mature operational capabilities.
Physics Informed Machine Learning (PIML) is a modeling approach that harnesses the power of machine learning and big data to improve the understanding of coupled, dynamic systems.
PNNL data scientists and engineers will be presenting at NeurIPS, the Thirty Fourth Conference on Neural Information Processing Systems, and the co-located Women in Machine Learning workshop, WiML.
PNNL researchers developed and manage the online database Tethys to actively collects and curates information on the environmental effects of wind and marine energy.
PNNL creates immersive software experiences to meet a variety of challenges. One such challenge in science, technology, engineering, and mathematics (STEM) education is providing quality computer science education for all students.
PNNL develops training, exercises, and assessments to prepare and equip border security officers to detect, identify, and interdict the illicit movements of materials, commodities, and components associated with WMD.
