Tianyuan Cai

Tianyuan Cai is a research engineer at Adobe Research. His research focuses on leveraging Human-computer collaborations to improve the user experience when consuming digital content. He takes an interdisciplinary approach to research, with toolkits spanning crowdsourcing, prototyping, and perceptual user studies.

AI & Machine Learning Human Computer Interaction

Publications

April 30, 2023 Proceedings of the ACM Web Conference 2023

Web Table Formatting Affects Readability on Mobile Devices

Chris Tensmeyer, Zoya Bylinskii, Tianyuan Cai, Dave Miller, Ani Nenkova, Aleena Gertrudes Niklaus, Shaun Wallace

April 19, 2023 Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Digital Reading Rulers: Evaluating Inclusively Designed Rulers for Readers With Dyslexia and Without

Aleena Gertrudes Niklaus, Tianyuan Cai, Zoya Bylinskii, Shaun Wallace, Bylinskii

April 19, 2023 Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

THERIF: Themes for Readability from Iterative Feedback

Tianyuan Cai, Aleena Gertrudes Niklaus, Bernard Kerr, Michael Kraley, Zoya Bylinskii

December 1, 2022 Foundations and Trends in Human–Computer Interaction

Readability Research: An Interdisciplinary Approach

Sofie Beier, Sam Berlow, Esat Boucaud, Zoya Bylinskii, Tianyuan Cai, Jenae Cohn, Kathy Crowley, Stephanie L. Day, Tilman Dingler, Jonathan Dobres, Jennifer Healey, Rajiv Jain, Marjorie Jordan, Bernard Kerr, Qisheng Li, Dave B. Miller, Susanne Nobles, Alexandra Papoutsaki, Jing Qian, Tina Rezvanian, Shelley Rodrigo, Ben D. Sawyer, Shannon M. Sheppard, Bram Stein, Rick Trietman, Jen Vanek, Shaun Wallace, Benjamin Wolfe

June 13, 2022 Designing Interactive Systems Conference (DIS)

Personalized Font Recommendations: Combining ML and Typographic Guidelines to Optimize Readability

Tianyuan Cai, Shaun Wallace, Tina Rezvanian, Jonathan Dobres, Bernard Kerr, Samuel Berlow, Jeff Huang, Ben D Sawyer, Zoya Bylinskii