Lab Partnering Service Discovery
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She leads the Data Science Engagement Group at the National Energy Research Scientific Computing Center (NERSC) at Berkeley National Lab. A native of the U.K., her career spans research in particle physics, cosmology, and computing on both sides of the Atlantic. She obtained her Ph.D. at Edinburgh University, and worked at Imperial College London and SLAC National Accelerator Laboratory before joining NERSC. Her group leads the support of supercomputing for experimental science, and her work focuses on data-intensive computing and research. This includes using high-performance computing (HPC) to scale up machine-learning algorithms that can tackle new, larger scientific problems; and leveraging artificial intelligence to gain insight from cosmological data.
Nicola Ferrier received her doctorate from Harvard University in 1992. After postdoctoral fellowships at Oxford University and Harvard, she joined the Department of Mechanical Engineering at the University of Wisconsin (UW)-Madison in 1996. She became an associate professor in 2003 and professor in 2009. She received the NSF CAREER award (1997) and the UW Vilas Associates Professorship (1999) and the UW Honored Instructor Award (2009). She joined the Mathematics and Computer Science Division at Argonne in 2013.
Ferrier’s research interests are in the use of computer vision (digital images) to control robots, machinery, and devices, with applications as diverse as medical systems, manufacturing, and projects that facilitate “scientific discovery” (such as her recent project using machine vision and robotics for plant phenotype studies).
Title: Assistant Computational Scientist
- Scientific literature processing to rapidly find protein-protein interaction candidates
- AI-based platform to accelerate discovery of novel drug compounds
- Querying and filtering interface for users to efficiently scan tens of thousands of sources
Since joining Brookhaven National Laboratory in 2018, Carlos X. Soto has been an active member of the Machine Learning Group, where he has contributed extensively toward large-scale scientific data extraction from published literature using natural language processing (NLP) techniques applied to areas such as functional genomics, drug discovery, and government reports. His contributions to machine learning for the integration of biological genomics data helped prompt an ongoing partnership with Oak Ridge National Laboratory to use NLP techniques to accelerate COVID-19 drug discovery. In 2019, Soto was part of the Brookhaven team awarded one of only two Nuclear Threat Initiative (NTI) Nuclear Security Index Challenge grants. The work, Towards a Predictive Nuclear Security Threat Model, aims to create a predictive model by integrating NTI Index data into machine learning and sentiment analysis. Presently, his work on COVID-related projects focuses on providing domain scientists with powerful new computational tools to identify patterns and insights in large volumes of documents, in particular relating to potential drug compound candidates.
During his career with NETL, U.S. Army veteran Jimmy Thornton has worked tirelessly to advance new technology development for Fossil Energy (FE), and that remains true today with current efforts to investigate uses for artificial intelligence (AI) and machine learning (ML) for FE technology development.
Born in Kentucky and growing up in Campbells Creek, Thornton joined the U.S. Army at the encouragement of his high school baseball coach who was an Army Reserve drill instructor. Trained as an infantryman and entering service in early 1983, Thornton was stationed in Germany, where he completed French Commando School in Givet, France.
Leaving active service in 1987, Thornton joined the Kentucky National Guard while studying at Eastern Kentucky University, and he later transferred to the West Virginia National Guard after accepting a professional internship with the U.S. Department of Energy (DOE) in Morgantown in 1988. Commissioned as an officer in 1992, he served with the 201st Field Artillery and was deployed to Iraq in 2004 during Operation Iraqi Freedom.
Achieving the rank of major, Thornton retired in 2010 with more than 27 years of service and continues to serve the 201st as an active member of the 201st Association. He said many of the skills and life lessons the army taught him continue to guide him at NETL, where he started working in 1991 when it was known as the Morgantown Energy Technology Center.
Thornton’s work at the Lab as associate director for the Computational Science and Engineering directorate includes advances in applied artificial intelligence, and machine learning, which he said have great potential to benefit the country’s energy industries, especially the existing fleet of coal-fired power plants and the subsurface. He noted that increased data availability and the use of supercomputers can speed up the development cycle of new tools for decision making because machine learning techniques can provide insights beyond our current understanding.