AI/ML research funding
Department of Energy Funds Five Research Projects on Artificial Intelligence and Machine Learning
The Department of Energy is providing a total of $16 million for five research projects aimed at developing artificial intelligence and machine learning algorithms that will enable scientific insights and discoveries using data produced by computation simulations, experiments and observations.
The projects will produce capabilities for a broad range of scientific needs, including forecasts for the dynamic behavior of the electric power grid, extreme climate and weather event predictions and using data produced by computational models for drawing conclusions about combustion, cosmology and high-energy physics, the DOE said Thursday.
According to Barbara Helland, the DOE Office of Science’s associate director for advanced scientific computing research, changes in disruptive technology are occurring across the ecosystems of high-performance computing, science applications, algorithms and architectures.
The projects that will receive DOD funding will help and automate scientific discovery and data analysis for problems that continue to evolve, Helland said.
The projects are led by eight universities and four national laboratories.
The research efforts were chosen by a competitive peer review under the funding opportunity announcement titled “Data-Intensive Scientific Machine Learning and Analysis.”
The funds are sponsored by the Office of Advanced Scientific Computing Research, which is under the DOE’s Office of Science.
The $16M awards are the latest in a series of scientific ML and AI funding opportunities that focus on ML-enhanced modeling and simulation, uncertainty quantification and intelligent automation and decision-support for complex systems.
Category: Federal Civilian
Tags: AI artificial intelligence Barbara Helland computational models cosmology Department of Energy DoE electric power grid federal civilian forecasts High Energy Physics machine learning ML Office of Advanced Scientific Computing Research Office of Science research projects weather predictions