Amir Gholami is a senior research fellow at ICSI and Berkeley AI Research (BAIR). He received his PhD from UT Austin, working on large scale 3D image segmentation, a research topic which received UT Austin’s best doctoral dissertation award in 2018. He is a Melosh Medal finalist, the recipient of best student paper award in SC'17, Gold Medal in the ACM Student Research Competition, as well as best student paper finalist in SC’14. Amir is a recognized expert in industry with long lasting contributions. He was part of the Nvidia team that for the first time made FP16 training possible, enabling more than 10x increase in compute power through tensor cores. That technology has been widely adopted in GPUs today. Amir's current research focuses on exa-scale neural network training and efficient inference.
Machine Learning, Deep Learning and Artificial Intelligence