GAMES Webinar 2023 – 280期(可视化中的人因问题:信任关系与沉浸感知) | 赵洁琼(PostDoc at Arizona State University),杨亚龙(Georgia Tech , Virginia Tech)

【GAMES Webinar 2023-280期】(可视化专题-可视化中的人因问题:信任关系与沉浸感知)

报告嘉宾:赵洁琼(PostDoc at Arizona State University)


报告题目:Trust Calibration in Human-Machine Teaming: Exploring Uncertainty Visualization and Beyond


Artificial intelligence or machine learning (AI/ML) models have gained traction as decision support tools that can process tremendous amounts of data that would be otherwise impossible to use. However, despite the benefits of automation, human experts are often tasked to corroborate information from the model predictions to provide a final decision since no AI/ML model is perfect. To achieve good performance in a human-machine teaming environment, humans have to appropriately use predictions made by AI/ML models. Consequently, it is crucial to present model predictions in a manner that assists humans in discerning when to rely on model predictions and when to identify potential flaws. In this talk, I primarily present a recent publication that investigates whether uncertainty visualization can effectively calibrate trust between humans and AI/ML models. Additionally, I will discuss future research directions for quantitatively exploring other factors that contribute to trust calibration.


Jieqiong Zhao is a postdoctoral research associate in the School of Computing and Augmented Intelligence at Arizona State University. She received her Ph.D. degree in Electrical and Computer Engineering from Purdue University in 2020 and her M.S. degree in Computer Science from Tufts University in 2013. Her research interests lie within the broad spectrum of data visualization and human-computer interaction. She specializes in developing new approaches for human-AI teaming and studying how to calibrate trust between humans and AIs within such human-AI teaming environments. Her research findings have been published in top-tier visualization and human-computer interaction venues, including IEEE TVCG, IEEE VAST, and ACM CHI. She contributes to the visualization community by reviewing papers for conferences such as IEEE VIS, EuroVis, and PacificiVis.


报告嘉宾:杨亚龙(Georgia Tech , Virginia Tech)


报告题目:Data Visualization in the Metaverse: What, Why, and How?


Data visualization is the process of converting complex raw data into meaningful graphics. Leveraging the powerful human visual system to summarize information in a cognitively efficient way, visualization becomes ubiquitous in science, analysis, and media. A long-standing core research question in visualization research is how to design novel and effective visualizations. Display and interaction technologies define how data can be visually represented and how people can interact with them. As an emerging display and interaction platform, VR/AR provides unparalleled potential for renewing our human-data interaction experience.

This talk will present novel visualization and interaction techniques for the metaverse. The presentation will first discuss unique characteristics in VR/AR that conventional 2D displays cannot offer, in the context of data visualization. The presenter will then exemplify how to take advantage of those features to build novel and effective visualizations in VR/AR. Finally, the presenter will describe the vision of the future workspace, where VR/AR will be an essential component, and conclude on an optimistic note: with deep integration between hardware, software, and user experience, we can achieve this vision in the near future.


Yalong Yang is joining the School of Interactive Computing at Georgia Tech as an Assistant Professor in 2023 Fall. He has been an Assistant Professor at Virginia Tech from August 2021. Prior to this, He was a Postdoctoral Fellow in the Visual Computing Group at Harvard University, and received his Ph.D. from Human-Centred Computing Department, Monash University, Australia.

His research encompasses a wide range of topics within the fields of Visualization (VIS), VR/AR, and Human-Computer Interaction (HCI). He actively contributes to these communities and regularly publish his work in leading venues such as IEEE VIS, ACM CHI, IEEE TVCG, EuroVis, and IEEE VR. He has received three best paper honorable mention awards, notably from IEEE VIS in 2016 and 2022, as well as ACM CHI in 2021. He also serves as a Program Committee member for several prestigious conferences in his fields, including IEEE VIS 2022/23, ACM CHI 2023, and IEEE VR 2022/23. He is also one of the online experience chairs for ISMAR 2023.



马昱欣,南方科技大学计算机科学与工程系副教授、研究员。主要研究方向为数据可视化、可视分析、可解释人工智能,发表论文20余篇,在TVCG、IEEE VIS、CHI等国际重要期刊会议上发表多篇长文,曾获得ACM CHI 2022最佳论文提名、CVMJ期刊年度最佳论文提名等奖项。目前担任CCF CADCG、CSIG-VIS专委会委员,以及国内外可视化相关会议的程序委员。长期担任IEEE VIS、TVCG、CG&A等期刊会议的审稿人。更多信息可见


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