Design Guidelines and Human-AI Collaboration for Data Storytelling
Prof. Huamin Qu
Hong Kong University of Science and Technology

Chair: Issei Fujishiro

9:30-10:30, April 24
Data storytelling involves crafting a compelling story around data, using a combination of visualizations, text, and multimedia elements to convey a message that resonates with the audience. In this keynote, we will present our research on data storytelling, focusing on guidelines for crafting effective openings and endings in data videos, using Freytag’s Pyramid to create structured data stories, and exploring the potential of human-AI collaboration in data storytelling. We will share insights on creating effective data-GIFs and provide suggestions for improving their understandability. Drawing on cinematic arts, we will present guidelines for creating cinematic openings and endings in data videos. Finally, we will discuss the potential of AI to support humans in data storytelling and identify research opportunities for human-AI collaboration in this field.

Huamin Qu is the dean of the Academy of Interdisciplinary Studies (AIS), the head of the Division of Emerging Interdisciplinary Areas (EMIA), and a chair professor in the Department of Computer Science and Engineering (CSE) at the Hong Kong University of Science and Technology (HKUST). He holds a BS in Mathematics from Xi’an Jiaotong University, as well as an MS and a PhD in Computer Science from Stony Brook University. His research focuses on visualization and human-computer interaction, and he has been recognized with many awards, including the IEEE VGTC Technical Achievement Award, 15 best paper/honorable mention awards, and AI 2000 Most Influential Scholar in Visualization Awards. He has mentored 40 PhD graduates, 17 of whom now hold faculty positions at major universities in China, Singapore, the UK, and the USA. In 2020, he was inducted into the IEEE Visualization Academy.

Human-Data Interaction: Data Visualization and Beyond
Prof. Bongshin Lee
Yonsei University

Chair: Kwan-Liu Ma

09:00-10:00, April 26
Data plays a pivotal role in our daily lives, offering vast possibilities to shape our work, lifestyles, and interactions with the world. Over the last few decades, data visualization has proven to be a powerful tool for gaining and communicating insights, as well as facilitating informed decision-making in diverse fields and contexts. However, visualization research has traditionally centered on narrow aspects of how people interact with data. Much of the research has focused on desktop environments designed for data experts and individuals without disabilities, overlooking the diverse human capabilities and needs. In this talk, I advocate for expanding the scope of our research endeavors to cover a wider range of activities and contexts in which individuals interact with data, aiming to serve a more diverse audience. I will illustrate how my research has evolved from concentrated efforts in data visualization to a broader exploration in human-data interaction. I will present recent projects on novel and inclusive data interaction experiences that leverage advancements in input technologies and AI. I will also suggest exciting research avenues we can pursue to enrich data interaction experiences, going beyond data visualization, for a wider audience, which will also help to make data and data visualization accessible and beneficial to everyone.

Bongshin Lee is a Professor at Yonsei University in Seoul, Korea, since March 2024. Before this, she was a Senior Principal Researcher at Microsoft Research in Redmond, USA. Lee conducts research on data visualization, human-computer interaction, and human-data interaction, with an overarching goal to empower everyone to achieve their goals by leveraging data, visualization, and technological advancements. She explores innovative ways to help people interact with data, by supporting easy and effective data collection, data exploration & analysis, and data-driven communication. Lee is the Chair of the IEEE VGTC (Visualization and Graphics Technical Community) and a member of the ACM ISS Steering Committee, and currently serves as the Papers Co-Chair for CHI 2025. She served as the General Co-Chair for ISS 2019 and IEEE PacificVis 2017, Subcommittee Co-Chair for ACM CHI 2021 & 2022 (for the Visualization Subcommittee), Overall Papers Co-Chair for VIS 2021 & 2022, as well as Papers Co-Chair for IEEE InfoVis 2015 & 2016, and IEEE PacificVis 2018. Lee was inducted into the IEEE Visualization Academy in 2020. She received her PhD in Computer Science from the University of Maryland at College Park in 2006.