![](https://www.usenix.org/sites/default/files/styles/board_bio_photo/public/wu_carole_jean_200x230.jpg?itok=2h9zc7yu)
Carole-Jean Wu is a Director at Meta. She is a founding member and a Vice President of MLCommons—a non-profit organization that aims to accelerate machine learning for the benefit of all. Dr. Wu also serves on the MLCommons Board as a Director, chaired the MLPerf Recommendation Benchmark Advisory Board, and co-chaired for MLPerf Inference. Prior to Meta/Facebook, She was a tenured professor at ASU. She earned her M.A. and Ph.D. from Princeton and B.Sc. from Cornell.
Dr. Wu's expertise sits at the intersection of computer architecture and machine learning. Her work spans across datacenter infrastructures and edge systems, such as developing energy- and memory-efficient systems and microarchitectures, optimizing systems for machine learning execution at-scale, and designing learning-based approaches for system design and optimization. Dr. Wu's work has been recognized with several awards, including IEEE Micro Top Picks and ACM/IEEE Best Paper Awards. She was the Program Co-Chair of the Conference on Machine Learning and Systems (MLSys) in 2022, the Program Chair of the IEEE International Symposium on Workload Characterization (IISWC) in 2018, and the Editor for the IEEE MICRO Special Issue on Environmentally Sustainable Computing. She currently serves on the ACM SIGARCH/SIGMICRO CARES committee.