모바일 메뉴 닫기
 
News

알림마당

학부공지

제목
5월 12일 컴퓨터과학과 정기 수요 세미나 (온라인) : Empower Humans to Steer Deep Neural Networks with Human-in-the-loop Approaches and Int
작성일
2021.05.07
작성자
컴퓨터과학과 홈페이지 관리자
게시글 내용



공지 내용

제목: Empower Humans to Steer Deep Neural Networks with Human-in-the-loop Approaches and Interactive Tools

강사: Prof. Sungsoo Ray Hong (George Mason University)

일시: 2021년 5월 12일 (수요일) 오후 5시

링크: https://yonsei.zoom.us/j/83702962099?pwd=Nk5MSzFOT3pDZHJJKzNDUytXNHBWZz09


Abstract:

As the use of machine learning models in product development and data-driven decision-making processes became pervasive in many application domains, people's focus on building a well-performing model has rapidly shifted to understanding how their model works. Recent years have seen an explosion of interest in understanding how Deep Neural Networks (DNNs) work under the hood and more importantly, how we can adjust the way DNNs work based on our knowledge and expectation. However, DNNs' architecture offers limited transparency, imposing significant challenges in (1) determining when DNNs make unsuccessful predictions with potential bias and more importantly, and (2) improving the model to make the future behavior align with human expectation. In this talk, I will introduce my approach and vision towards establishing an interactive platform that assists data scientists in steering DNNs in a more cost-efficient, effective, and useful way. At the beginning of the talk, I introduce a formative study that aimed at deeply understanding the current practice of data scientists who apply explainable AI tools in designing, building, and deploying machine learning models. Then I introduce my recent approaches focusing on leveraging interactive attention mechanisms towards empowering users to better steering DNNs in the stage of data collection/annotation and model building stages.


Bio:

Ray Hong is an Assistant Professor at the Department of Information Sciences and Technology at George Mason University. He earned his Ph.D. in Human-Centered Design and Engineering at the University of Washington. In Mason, he directs the Alignment lab where members focusing on bridging the gap between humans' mental models and the way that AI operates by designing novel tools and establishing theories in Human-Computer Interaction (HCI) and Computer-supported Cooperative Work (CSCW). His ultimate mission is to improve the way people interact with and tune AIs to have trustworthy and unbiased insights and decisions. Before joining the University of Washington, he had 5 years of industry experience at Samsung Research where he contributed to commercializing digital products adopted in Samsung’s millions of mobile and home devices.