Is pre-training the key to successful domain generalization?
Kate Saenko
2024 Invited Talk
in
Workshop: Adaptive Foundation Models: Evolving AI for Personalized and Efficient Learning
in
Workshop: Adaptive Foundation Models: Evolving AI for Personalized and Efficient Learning
Speaker
Kate Saenko
Kate is an AI Research Scientist at FAIR, Meta and a Full Professor of Computer Science at Boston University (currently on leave) where she leads the Computer Vision and Learning Group. Kate received a PhD in EECS from MIT and did postdoctoral training at UC Berkeley and Harvard. Her research interests are in Artificial Intelligence with a focus on out-of-distribution learning, dataset bias, domain adaptation, vision and language understanding, and other topics in deep learning. Past academic positions Consulting professor at the MIT-IBM Watson AI Lab 2019-2022. Assistant Professor, Computer Science Department at UMass Lowell Postdoctoral Researcher, International Computer Science Institute Visiting Scholar, UC Berkeley EECS Visiting Postdoctoral Fellow, SEAS, Harvard University
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