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Wenbo He "Making Machine Learning Trustworthy in Vision Tasks"

Event Type
Illinois Computer Science
2405 Siebel Center for Computer Science
Oct 31, 2023   10:30 am  
Wenbo He, Associate Professor in the Department of Computing and Software, McMaster University
Candice Steidinger
Originating Calendar
Computer Science Speakers Calendar

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Abstract: Recently, machine learning (ML) performance has drastically increased as a result of powerful computing facilities and large datasets. However, the inherent weaknesses in the reliability and security of data-centric machine learning applications may result in performance degradation, system misbehavior, and/or privacy breach. Building trustworthy data-centric learning systems is among the biggest and most impactful challenges in the next decade. In this talk I will briefly introduce several of our recent projects addressing learning with noisy labels, learning with small data, and learning with privacy concerns, respectively. We seek to formulate the trustworthy machine learning problems and design solutions to ensure the robustness, trustworthiness, and privacy of data-centric machine learning systems.

Bio: Wenbo He is currently an Associate Professor in the Department of Computing and Software. Before joining McMaster, she was an Assistant Professor in the School of Computer Science at McGill University from 2011 to 2016. She was an Assistant Professor in the Electrical Engineering department at the University of Nebraska-Lincoln from 2010 to 2011, and an Assistant Professor in the CS department at the University of New Mexico from 2008 to 2010. She had 5-year industry experience (2000-2005) working in Cisco Systems, Inc. in the US. She got the bachelor's and master's Degree on Control Theory in 1995 and 1998 respectively. She got her Ph.D. in 2008 from the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC). She received the Mavis Memorial Fund Scholarship Award from the College of Engineering of UIUC in 2006 for “excellent academic performance, research accomplishments, and demonstrated leadership in engineering education”, and the C. W. Gear Outstanding Graduate Award in 2007 for “being one of the best graduate students from the UIUC Department of Computer Science”. Her papers won the Best Paper Award from IEEE Transactions on Industrial Informatics in 2008, and the Best Paper Award from ACM WiSec 2011. Her research focuses include big data systems, CPS systems, and trustworthy ML.

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