Diane Feddema is a Principal Software Engineer at Red Hat leading performance analysis and visualization for the Red Hat OpenShift Data Science (RHODS) managed service. She is also a working group chair for the MLCommons Best Practices working group and the CNCF SIG Runtimes working group.

She also creates experiments comparing different types of infrastructure and software frameworks to validate reference architectures for machine learning workloads using MLPerf™. Previously, Feddema was a performance engineer at the National Center for Atmospheric Research, NCAR, working on optimizations and tuning of parallel global climate models. She also worked at SGI and Cray on performance and compilers.

She has a bachelor's in Computer Science from the University of Iowa and master's in Computer Science from the University of Colorado.