Event Details - "Human-Centered Machine Intelligence" with Leqi Liu '17

Join the Libraries and the Math department for a Young Academic Alumni Lecture by Leqi Liu '17!

This will be a hybrid talk; join the Zoom here.

Abstract: Building machine intelligence from a human-centered perspective is increasingly urgent, as large-scale machine learning systems ranging from personalized recommender systems to language and image generative models are deployed to interact with people daily. In this talk, I will give an overview of the field of human-centered machine intelligence. Using examples ranging from decision-support systems in healthcare to personalized recommender systems in online platforms to large-language models, I will showcase how we can account for complex human preferences in designing algorithms for building these systems. I will conclude the talk by discussing open questions and the role of interdisciplinary research in this field.

Leqi Liu is a postdoctoral researcher at Princeton’s Center for Language and Intelligence, working on understanding and building large language models. She will join University of Texas at Austin as an assistant professor in Fall 2024. She graduated from the machine learning department at CMU this past summer. During her Ph.D., she studies the foundations of human-centered machine learning, using insights from behavioral sciences and tools from learning theory to design machine learning algorithms that account for complex human preferences. She has spent time at Google DeepMind and Apple during her Ph.D., and majored in mathematics at Haverford College and computer science at Bryn Mawr College. 

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