Anqi “Angie” Liu is an assistant professor in the Department of Computer Science at the Whiting School of Engineering. She is broadly interested in developing principled machine learning algorithms for building more reliable, trustworthy, and human-compatible AI systems in the real world. Her research focuses on enabling the machine learning algorithms to be robust to the changing data and environments, to provide accurate and honest uncertainty estimates, and to consider human preferences and values in AI interactions. She is particularly interested in high-stake applications that concern the safety and societal impact of AI.
Liu develops, analyzes, and applies methods in statistical machine learning, deep learning, and sequential decision-making. One established line of her work is in distributionally robust learning under covariate shift. Her recent projects cover topics in different types of distribution shifts, active learning, safe exploration, off-policy learning, fair machine learning, semi-supervised learning, cost-sensitive classification, and hierarchical classification.
Liu has won a number of awards, including an Amazon Research Award, a Johns Hopkins University + Amazon Initiative for Artificial Intelligence Faculty Research Award, a Johns Hopkins Discovery Award, and a Johns Hopkins Institute for Assured Autonomy Challenge Grant. She was also selected as one of the 2020 Rising Stars in electrical engineering and computer science, and her publications have appeared in prominent machine learning venues like the Conference on Neural Information Processing Systems, the International Conference on Machine Learning, the International Conference on Learning Representations, the Association for the Advancement of Artificial Intelligence, and the Society for Artificial Intelligence and Statistics.
Her research on applying machine learning to health care has been supported by the National Institute on Aging and the Moore Foundation. Liu is also core faculty in the National Institutes of Health Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity Program and serves on program committees and as area chair for several conferences in machine learning.
Liu obtained her PhD in computer science from the University of Illinois Chicago. Prior to joining Johns Hopkins, she completed her postdoctoral research in the Department of Computing + Mathematical Sciences at the California Institute of Technology.
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Putting trust to the test
CategoriesHopkins researchers unveil new uncertainty quantification methods in an effort to promote appropriate trust in AI use.
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Winning project teams—chosen from 191 proposals—include 115 individuals from across the university.