Predicting how organisms’ characteristics respond to not only their genes, but also their environments (a nascent field called predictive phenomics), is extraordinarily challenging. Researchers at PNNL are using AI to tackle that challenge.
Aaron Luttman and Jonathan Forman represented PNNL at the high-profile "Risk and Reduction Science and Policy Forum" organized by Johns Hopkins University and supported by the Defense Threat Reduction Agency.
Jonathan Barr, senior systems engineer at PNNL, was recently invited to co-present on a panel at the Texas Department of Emergency Management Annual Conference.
John VerWey, an advisor in the Mission Alignment group at PNNL, has recently been selected to lead a panel discussion at the inaugural Special Competitive Studies Project (SCSP) AI+ Compute & Connectivity Summit.
Lauren Charles, a chief data scientist at PNNL, showcased the vital research coming out of her program at The National Academies Forum workshop in Washington, D.C., January 15–16, 2025.
PNNL's ASSORT model will help airports balance passenger screening and security risks with throughput. It also quantifies risks for different traveler types and optimizes checkpoint operations, improving efficiency while enhancing safety.
Over the next four years, PNNL and University of Arizona will develop open-source computational tools to better identify and characterize the viruses associated with the human microbiome.
Sergei Kalinin, a joint appointee at the University of Tennessee, Knoxville and PNNL, and Ji-Guang (Jason) Zhang, a PNNL Lab Fellow, are part of the 2024 class of National Academy of Inventors Fellows.
