PNNL has received 119 R&D 100 Awards since 1969, when the laboratory began submitting entries in the contest that recognizes top 100 inventions each year.
Researchers at PNNL examined heat pump water heater (HPWH) operation in Pacific Northwest residences, gaining insights into HPWH electricity use patterns. Part of the study captured trends during a COVID-19 stay-at-home order.
A team of PNNL researchers are looking at how to evaluate robustness and accountability, fairness, and transparency of artificial intelligence models used to detect and quantify deceptive content online.
A Q&A with Lauren Charles, veterinarian and PNNL data scientist, on zoonotic diseases and the role biosurveillance plays in mitigating the growing threat to global health.
More than 30 PNNL interns contributed to the Airport Risk Assessment Model, a web-based tool that helps airport security stakeholders prioritize resource allocations.
The Washington State Academy of Sciences consists of more than 300 elected members who are nationally recognized for their scientific and technical expertise.
Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.
PNNL’s energy-efficient dehumidifier may reduce energy consumption by up to 50% in residential A/C systems and increase the range of electric vehicles by up to 75%. The system has been licensed to Montana Technologies.
Svitlana Volkova, chief scientist for decision intelligence and analytics at PNNL, was invited as a panelist at the SIAM International Conference on Data Mining
PNNL data scientists Svitlana Volkova and Emily Saldanha, along with former PNNL intern Pamela Bilo Thomas, will publish their research on online information spread in Nature's Scientific Reports.
Michael Henry, a senior data scientist at PNNL, has accepted a joint appointment at the Texas A&M University RELLIS Center for Applied Research and Experiential Learning.
PNNL data scientists Henry Kvinge and Ted Fujimoto presented their research on few-shot learning and reinforcement learning, respectively, at workshops during the 2021 AAAI Conference on Artificial Intelligence.