Yuhong Guo
Canada CIFAR AI Chair
Academic Affiliations
Industry and Research Affiliations
Areas of Expertise
Canada CIFAR AI Chair
Academic Affiliations
Industry and Research Affiliations
Areas of Expertise
Yuhong Guo's ultimate research goal is to automate the learning process and reduce the dependence of learning systems on human guidance
Working within the field of machine learning, Yuhong Guo focuses on learning useful data representations and accurate classification models under various circumstances. Her ultimate research goal is to automate the learning process and reduce the dependence of learning systems on human guidance. Her research program has been founded on three main directions: generalized transfer learning, learning from incomplete data, and learning from weakly supervised data. In her work on transfer learning, Yuhong has leveraged auxiliary data resources to reduce the annotation requirement for target tasks, via domain adaptation, zero-shot and few-shot learning. For data analysis scenarios, such as recommender systems, where the data is naturally sparse and contains missing entries, she has developed matrix completion techniques to infer the underlying data association mechanisms and automatically recover missing observations. She has also developed techniques that can learn accurate prediction models from weak supervision such as imprecise annotations collected via crowdsourcing from non-experts.
Yuhong is a Canada CIFAR AI Chair at Amii, a Professor in the School of Computer Science at Carleton University and a Canada Research Chair in Machine Learning. She is an Associate Editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence and is on the Editorial Board of the Artificial Intelligence Journal. She has served as a Senior Program Committee member and Area Chair for AAAI, IJCAI and ACML, and has served on the program committees for many other international conferences, including NeurIPS, ICML, ICLR, UAI, ACL, CVPR and ICCV. Yuhong has had more than 80 papers published in top-tier scientific journals and conferences and, since 2007, has supervised more than 20 early-career researchers at the M.Sc and Ph.D. levels. Her research has received best paper awards from multiple international conferences.
Jul 13th 2021
News
The work of Amii researchers is being featured at the 38th annual International Conference on Machine Learning (ICML), running online this year from July 18 to 24.
Jul 13th 2021
Research Post
Jan 19th 2021
News
As part of the January 2021 AICan, Amii is pleased to welcome 15 new Canada CIFAR AI Chairs into our research community.
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