Prof. Melanie Tory, Northeastern University
Envisioning cooperative visualization systems
Time and Location: May 30th, 9 – 10am – Room B150, Bob Wright Building
Abstract: Cooperative behavior is a key aspect of human communication and collaboration: we anticipate each other’s needs and take active steps to support other people. In contrast, most computing systems, including data visualization tools, are reactive — they simply do what we ask. In this talk I will argue that visualization systems can have greater impact by moving beyond interactive visual data displays, to become cooperative partners in the analytical workflow. How might a future cooperative visualization system behave? I will explore this question, drawing on examples such as chatbots, dashboards, and visualization recommendation systems.
Bio: Melanie Tory is Director of Data Visualization Research at the Roux Institute, Northeastern University. Her team focuses on empowering people to do more with data, through the design and evaluation of novel visualization techniques, human-data interactions, and technology interfaces. She is especially focused on visualizations for health and engineering applications, and the interplay between visualization and AI. In her previous role at Tableau, Melanie managed an applied user research team and conducted research in natural language interaction with visualizations, ultimately commercialized as Tableau’s Ask Data feature. From 2006-2015, she worked as a faculty member in visualization at the University of Victoria, where she explored topics such as collaborative and personal visual analytics. Melanie earned her PhD in Computer Science from Simon Fraser University and her BSc from the University of British Columbia. She is Associate Editor of IEEE Computer Graphics and Applications and IEEE Transactions on Visualization & Computer Graphics, and has served as Papers Co-chair for the IEEE Information Visualization, ACM Interactive Surfaces and Spaces, and Graphics Interface conferences.
Registration Link: https://www.eventbrite.ca/e/636806775207
Prof. Maneesh Agrawala, Stanford University
Unpredictable Black Boxes are Terrible Interfaces
Time and Location: June 2nd, 9 – 10am – Room B150, Bob Wright Building
Abstract: Modern generative AI models are capable of producing surprisingly high-quality text, images, video and even program code. Yet, the models are black boxes, making it impossible for users to build a mental model for how the AI works. Users have no way to predict how the black box transmutes input controls (e.g., natural language prompts) into the output text, images, video or code. Instead, users have to repeatedly create a prompt, apply the model to produce a result and then adjust the prompt and try again, until a suitable result is achieved. In this talk I’ll assert that such unpredictable black boxes are terrible interfaces and that they always will be until we can identify ways to explain how they work. I’ll also argue that the ambiguity of natural language and a lack of shared semantics between AI models and human users are partly to blame. Finally I’ll suggest some approaches for improving the interfaces to the AI models.
Bio: Maneesh Agrawala is the Forest Baskett Professor of Computer Science and Director of the Brown Institute for Media Innovation at Stanford University. He works on computer graphics, human computer interaction and visualization. His focus is on investigating how cognitive design principles can be used to improve the effectiveness of audio/visual media. The goals of this work are to discover the design principles and then instantiate them in both interactive and automated design tools. Honors include an Okawa Foundation Research Grant (2006), an Alfred P. Sloan Foundation Fellowship (2007), an NSF CAREER Award (2007), a SIGGRAPH Significant New Researcher Award (2008), a MacArthur Foundation Fellowship (2009), an Allen Distinguished Investigator Award (2014), induction into the SIGCHI Academy (2021), and being named an ACM Fellow (2022).
Registration Link: https://www.eventbrite.ca/e/636812452187
Prof. Craig Kaplan, University of Waterloo
An aperiodic monotile: new shape just dropped
Time and Location: June 2nd, 1 – 2:30pm – Room B150, Bob Wright Building
Abstract: A longstanding open problem in geometry asks whether it is possible for a single shape to be a periodic: to tile the plane without ever permitting translational symmetries. A recently discovered shape called the “hat” is just such an aperiodic monotile, settling this open problem in two dimensions. In this talk I will introduce some background concepts from tiling theory, present the history of the search for aperiodic shapes, and then discuss the discovery of the hat and its wonderful mathematical properties.
Bio: Craig S. Kaplan is an Associate Professor of Computer Science at the University of Waterloo. His research focuses on interactions between computer science, mathematics, and art, with an emphasis on tools and algorithms that generate ornamental patterns or that empower artists and designers. Craig is an associate editor and past editor-in-chief of Journal of Mathematics and the Arts, and helps organize the annual Bridges Conference on interdisciplinary math-art connections.
Registration Link: https://www.eventbrite.ca/e/636815802207
Dr. Lauren Cheatham, Roblox Research
Understanding the Role of Avatar and Identity in 3D Social Interaction and Co-experience
Time and Location: May 31st, 9 – 10am – Room B150, Bob Wright Building
Abstract: As more and more people engage with immersive virtual spaces we find that the role of avatars is adapting to the changing expectation of users. Avatars now provide individuals with unique possibilities to explore identities and define physical and psychological boundaries unencumbered by the constraints of non-virtual experiences. This still nascent virtual co-experience is rife with opportunity to help individuals, especially younger generations, not only establish a sense of self in a virtual world with endless possibilities, but also transfer that new sense of self into the physical world. In this talk Dr. Cheatham will discuss how and where identity integrates with avatar experiences today and where we might envision it for the future.
Bio: Lauren Cheatham is a behavioral scientist and principal quantitative researcher at Roblox. She received her PhD in Marketing with a focus on consumer behavior at Stanford’s Graduate School of Business. Prior to joining Roblox, she worked as a quantitative researcher at Instagram, a CX researcher and data scientist at Apple, and a Professor of marketing at the University of Hawaii.
GI 2022 Award Winners
Dr. Nicole Sultanum
Dr. Sultanum is the recipient of the 2022 award for Bill Buxton Best Canadian HCI Dissertation Award completed at a Canadian university in the field of Human-Computer Interaction. Dr. Sultanum’s dissertation, Text-centric Visual Approaches to Support Clinical Overview of Medical Text, innovates and integrates computational methods to support clinicians’ effective and efficient review of unstructured clinical note datasets.
Dr. Hsueh-Ti Derek Liu
Dr. Liu is the recipient of the 2022 Alain Fournier Award for Outstanding Doctoral Dissertation in Computer Graphics. Dr. Liu’s dissertation, titled Algorithms for Data-Driven Geometric Stylization & Acceleration, made outstanding contributions to the field of computer graphics.