Sayna Ebrahimi is a research scientist at Google. Her research focuses on tackling real-world large-scale data distributions while maximizing adaptation and generalization. She also develops label-efficient algorithms which reduce human effort while facilitate transfer of information through unsupervised and semi-supervised models. Before joining Google, she was a postdoctoral scholar at UC Berkeley working with Trevor Darrell. She also received her PhD from UC Berkeley in 2020. At Berkeley, her research was at the intersection of computer vision and machine learning with specialization in continual learning and domain adaptation.