Using machine learning to accelerate materials science

Machine learning can be a valuable tool for speeding up elements of the research process. It can be used to analyze data and create knowledge graphs and to surface the most relevant research for a specific research community. But as Dr. Alex Ganose, a postdoctoral researcher at Lawrence Berkeley National Laboratory (LBNL), points out, it needs to be deployed wisely. Alex's research involves using data science and machine learning to solve problems in materials science. "Most recently, I've developed a new framework to calculate electron lifetimes from first principles," he explained.