Toby Li
Director Of Human-Centered Responsible AI Lab (HRAI) at Lucy Family Institute for Data & Society
Notre Dame, Indiana, United States
Summary
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Senior🎓
Top SchoolToby Li is a human-centered AI researcher and assistant professor at the University of Notre Dame who directs the Human-Centered Responsible AI Lab, bringing 12 years of experience across HCI, ML, NLP, and end-user software engineering. He builds interactive systems that enable workers and non-experts to create, configure, and extend AI tools—turning research prototypes into real-world impact, as with his KITE chatbot work that influenced Azure services. A CMU Ph.D. in HCI with ties to leaders like Brad Myers and Tom Mitchell, Toby has published award-winning papers across HCI, NLP, and systems venues and collaborates with industry partners including Microsoft Research, IBM, Verizon, and J.P. Morgan. His recent focus adopts a bottom-up human-AI collaboration approach to address future-of-work challenges and democratize access to AI. Colleagues describe him as bridging rigorous user-centered methods with deployable engineering, pairing academic depth with practical product-minded outcomes.
12 years of coding experience
8 years of employment as a software developer
University of Minnesota Twin CitiesDoctor of Philosophy (Ph.D.), Human Computer Interaction, Doctor of Philosophy (Ph.D.), Human Computer Interaction at Carnegie Mellon University
English, Chinese
Github Skills (35)
accessibility10
forking10
smartphone10
pyautogui10
accessibility-api10
hierarchy10
procedures10
api10
android-app10
robustness10
error-handling10
watson-assistant10
wikipedia9
user-interface9
acl9
Programming languages (3)
Github contributions (5)
tobyli/wikibrain
Feb 2015 - Nov 2016
Contributions:332 commits, 2 PRs, 258 pushes in 1 year 9 months
arttechnologieslinesjava-librarystate-of-the-art
tobyli/Sugilite_development
Jun 2016 - Apr 2022
SUGILITE is a new programming-by-demonstration (PBD) system that enables users to create automation on smartphones. SUGILITE uses Android’s accessibility API to support automating arbitrary tasks in any Android app (or even across multiple apps). When the user gives verbal commands that SUGILITE does not know how to execute, the user can demonstrate by directly manipulating the regular apps’ user interface. By leveraging the verbal instructions, the demonstrated procedures, and the apps’ UI hierarchy structures, SUGILITE can automatically generalize the script from the recorded actions, so SUGILITE learns how to perform tasks with different variations and parameters from a single demonstration. Extensive error handling and context checking support forking the script when new situations are encountered, and provide robustness if the apps change their user interface. Our lab study suggests that users with little or no programming knowledge can successfully automate smartphone tasks using SUGILITE.
Contributions:389 commits, 24 PRs, 195 pushes in 5 years 11 months
robustnesswatson-assistantpbdaccessibilityparameters
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