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News and Highlights


Automating Expertise

Automating Expertise. ChemNet employs a new training approach that learns expert knowledge from large, initially unlabeled databases and outperforms current state-of-the-art supervised learning methods. Watch the video. Learn more.
September 2018

Neural Network Research Presented at Global Conference

Neural Network Research Presented at Global Conference. At the recent GiMLi 2018: Geometry in Machine Learning, Craig Bakker presented a poster on training methods for neural networks. GiMLi 2018 is co-located with the 35th International Conference on Machine Learning in Stockholm, Sweden, a premiere gathering for researchers in machine learning.
August 2018

Staff Present at Prestigious Artificial Intelligence Conference

Staff Present at Prestigious Artificial Intelligence Conference. Lawrence Phillips, Garrett Goh, and Nathan Hodas presented "Explanatory Masks for Neural Network Interpretability" recently at the International Joint Conference on Artificial Intelligence and the European Conference on Artificial Intelligence. A premiere gathering of researchers in artificial intelligence, IJCAI-ECAI-18 was held July 13 - 19 in Stockholm, Sweden.
August 2018

Chemception Poised to Change How Chemists See Molecules

Chemception Poised to Change How Chemists See Molecules. In a recent conversation with Chemistry World, Nathan Baker discussed Chemception, a deep convolutional neural network framework developed to predict a molecule's chemical properties from its structure. Read more.
August 2018

Four PNNL researchers participate in MATDAT18

Four PNNL researchers participate in MATDAT18, the Material and Data Science Hackathon. The three-day event is supported by the National Science Foundation. Bharat Medasani's research problem was accepted, one of only 21. Read more.
July 2018

Deep Learning Could Help Detect Nuclear Events Worldwide

Deep Learning Could Help Detect Nuclear Events Worldwide. PNNL scientists Emily Mace and Jesse Ward teamed to explore the promise of deep learning to help interpret signals from radioactive decay events, which could indicate underground nuclear testing. Mace presented their work at the 11th MARC conference — Methods and Applications of Radioanalytical Chemistry — in April 2018 in Hawaii. Read more.
July 2018


Curbing misinformation propagation on social media. Svitlana Volkova and Dustin Arendt, with collaborators, presented "Can You Verifi This? Studying Uncertainty and Decision-Making about Misinformation Using Visual Analytics" at ICSWM. Read more.
July 2018

Working to inform data choices

Working to inform data choices. Nathan Hodas participated in the National Library of Medicine of the National Institutes of Health (NIH) Data Science Drivers Workshop. Read the research proceedings.
July 2018

Training neural networks to classify low-background data

Training neural networks to classify low-background data. Emily Mace presented "Use of Neural Networks to Analyze Pulse Shape Data in Low-Background Detectors" at the Methods & Applications of Radioanalytical Chemistry (MARC) conference. Read more.
July 2018

Fuzzing research cited

Fuzzing research cited. As part of the Artificial Intelligence and Global Security Initiative, the Center for New America Security has published a series of reports related to the implications of the artificial intelligence revolution as it relates to global security. Read more.
July 2018

Teaching AI to Identify Clouds

Teaching AI to Identify Clouds. Co-PIs Donna Flynn and Erol Cromwell's (PCSD) work on developing an artificial intelligence (AI) system was recently featured in the Wall Street Journal, which reaches over 2.2 million readers. The system is being designed to distinguish clouds from other atmospheric constituents in lidar imagery. Read more.
May 2018

Svitlana Volkova

#Flu. Research highlighted in Scientific American. The April 2018 Scientific American, features work by NSD's Svitlana Volkova (Computing and Analytics Division) and team on predicting influenza outbreaks using social media. Read more.
April 2018

Aaron Tuor

Best Paper Finalist. "Protein Mutation Stability Ternary Classification using Neural Networks and Rigidity Analysis," was recognized as a Best Paper Award Finalist at BICOB 2018. The paper was authored by NSD's Aaron Tuor, with collaborators from Western Washington University. Read more.
March 2018

National Academies Roundtable

National Academies Roundtable. Nathan Hodas was an invited panelist at the National Academies of Sciences meeting: Artificial Intelligence and Machine Learning. Read more.
February 2018


Neural Information Processing Systems

NIPS. Researchers from the deep-learning group at PNNL hosted three presentations and a demo at NIPS, the annual Neural Information Processing Systems meeting on December 3-8, 2017. Read more.
December 2017

Women in Machine Learning workshop

WiML. Deep science researchers presented four posters at WiML, the annual Women in Machine Learning workshop held December 4-7, 2017. Read more.
December 2017

Supercomputing 2017

Supercomputing 2017. Court Corley was an invited speaker at the NVIDIA's SC17 booth, November 14, 2017. Read more.
November 2017

PNW Partnerships

PNW Partnership for Data Intensive Biomedical Science. The Deep Learning for Scientific Discovery Agile Investment team hosted the inaugural meeting of the PNW Partnership for Data Intensive Biomedical Science September 27-28, 2017. Read more.
September 2017

Second Annual Faculty Summit

Second Annual Faculty Summit. More than 40 researchers and educators gathered at PNNL June 14-15, 2017 for the second annual Computing@PNNL Faculty Summit, Machine Learning and Human Computer Interaction for Science and Security. Read more.
June 2017

Deep Learning