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Generative AI

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  3. Generative AI

Team

Nathan Hodas

Nathan Hodas

Investment Lead 

Nathan Hodas serves as the GenAI Investment lead. Hodas arrived at PNNL in 2014 after a postdoc at the Information Sciences Institute of the University of Southern California. His research focuses on machine learning, human-computer interaction, and scientific applications of AI.  His PhD focused on experimental and theoretic biophysics and nanoscale nonlinear optics. At the Information Sciences Institute, he studied social network dynamics and developed a human response dynamics approach to characterizing information spread. 

Thomas Grimes

Tom Grimes  

Chief Scientist

Tom Grimes serves as the science lead and Applied GenAI thrust lead for PNNL’s Generative AI investment. As a data scientist in the National Security Directorate, his research focuses on application and characterization of large language models and multimodal foundation models.

Paul Rigor

Paul Rigor 

Cloud-Based AI and High performance computing (HPC) Platforms Lead

Rigor serves as the Cloud-Based AI and HPC Platforms lead alongside Scott Godwin. He is a cloud architect within the Center for Cloud Computing group at PNNL. Currently, Rigor manages a portfolio of public–private partnerships among the major cloud service providers like Amazon Web Services, the Microsoft Azure Cloud, and the Google Cloud Platform. 

Scott Godwin

Scott Godwin 

Cloud-Based AI and HPC Platforms Lead

Godwin serves as the Cloud-Based AI and HPC Platforms lead alongside Paul Rigor. He is the director of the Center for Cloud Computing at PNNL. Godwin also served as the senior technical advisor and deputy to the Department of Energy’s chief information officer. In this capacity, he led the Department of Energy’s Data Center Modernization Initiative and workload migration to cloud infrastructure. 

Photo of Court Coirley

Court Corley 

Center for AI Director

Corley is the chief scientist for AI in the AI and Data Analytics Division at PNNL. Corley is a leader in the field of data science and biosurveillance, and his current work focuses on deep learning and narrow AI methods across the Department of Energy and U.S. government missions.

Research topics

Artificial Intelligence
Computing & Analytics
Future Computing Technologies
Global Nuclear & Radiological Security

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