[Colloquium] Zhuokai Zhao Dissertation Defense/ May 13th, 2024

[Devin Davis]

This is an announcement of Zhuokai Zhao’s Dissertation Defense
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Candidate: Zhuokai Zhao’s

Date: Monday, May 13th, 2024

Time: 9 am CT

Location: JCL 298

Title: Enhanced Data Utilization for Efficient and Trustworthy Deep Learning

Abstract: Deep learning (DL) has made significant impacts in many domains, including computer vision (CV), natural language processing (NLP), recommender systems, and many others. Besides the breakthroughs made to the model architectures, data has been another fundamental factor that significantly impacts the model performance. This emphasis on data has given rise to the concept of data-centric artificial intelligence (AI). Despite its growing importance, studies focusing on developing novel data utilization algorithms that enhance model performance without modifying its architecture are still lacking. Addressing this gap, this thesis proposes novel data utilization algorithms that correspond to different steps of the deep learning pipeline, ranging from data collection, formulation, to model training, evaluation, and to model inference as in many deployed applications. These algorithms aim to improve model performance, robustness, and trustworthiness through the lens of data utilization, while not altering model architectures or increasing computational or time costs.

Advisor: Yuxin Chen

Committee Members: Yuxin Chen, Bo Li, and Michael Maire
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