The Intelligent Adaptive Interventions Lab at the University of Toronto (led by Joseph Jay Williams) studies adaptive experimentation to design intelligent interventions for behavior change. We turn everyday explanations and prompts (e.g., on webpages, emails, SMS) into adaptive interventions by innovating on A/B testing - such as the AdapComp toolkit - and using algorithms that analyze data to deliver better versions to future users. Our work advances machine learning and statistical methods while spanning applied AI/ML, HCI, statistics, psychology, digital education, and mental health.
#Research Projects
We received a DSI (Data Science Institute) grant. Part of this is for crowdsourced interventions! We are working with 10+ researchers to bring their well-being intervention to life!
#Recent Accepted Publications
Two papers accepted to CHI' 24 on LLM Application, see them at www.intadaptint.org/papers!
#Highlights
We won the prestigious Xprize for transforming education through Perpetual-Experimentation. Read more at tiny.cc/ixprize and the paper tiny.cc/moocletpaper.
#Awards & ShoutOuts
Our QuickTA project combining AI (RL algorithms & #LLMs) with @TutorGen is one of 16 #ToolsCompetition finalists for the DARPA AI Tools for Adult Learning opportunity!
We gratefully acknowledge support from our sponsors:
Contact Us
Undergraduates & interested graduate students/postdocs interested in joining or collaborating, contact: iaiinterest@googlegroups.com.
Joseph can be contacted at
williams[at]cs[dot]toronto[dot]edu.