Isaac Lyngaas is a computational scientist in the Advanced Computing for Life Sciences & Engineering group of the Science Engagement section.
Prior to joining ORNL, Isaac received a PhD in computational science from Florida State University. His PhD research focused on the development of a Radial Basis Function quadrature method for solving nonlocal integral equations. He previously worked as a graduate research associate during his time at Florida State University and also spent a summer at the National Center for Atmospheric Research participating in the Summer internships in parallel computational science (SIParCS) program at the National Center for Atmospheric Research.
Isaac joined OLCF in 2019 as a Postdoctoral Research Associate at the Advanced Computing for Life Sciences & Engineering group. His research has focused on various aspects of computing in high performance computing environments including working with various machine learning workflows. His past work has included the development and porting of codes for the E3SM-MMF project to a performance portability library YAKL which he helped test and develop. Also, he has worked extensively with CANDLE ECP project developing, building, and testing of software for training Transformer machine learning models on existing and future OLCF systems. This work with transformer models is being used to model text based data in different aspects of scientific discovery including classification of cancer pathology reports and molecule generation in drug discovery.