About Me

Tiffany Wenting Li 李文婷

Computer Science Department
University of Illinois at Urbana-Champaign
Email: wenting7 [at] illinois [dot] edu
CV / Google Scholar / LinkedIn / Twitter

Affiliated Groups
Social Spaces Group
Crowd Dynamics Lab

I am a final-year Ph.D. student in Computer Science at the University of Illinois at Urbana-Champaign, co-advised by Professors Karrie Karahalios and Hari Sundaram. Previously, I completed my BA in Mathematics and Economics at Cornell University.

Research Keywords
Human-computer Interaction, Education, Human-centered AI, Algorithmic fairness, Natural Language Processing, Bayesian statistics, Causal inference, Mixed methods, Applied machine learning

Research Vision & Interests
What is computing’s role in providing equitable access to quality, personalized education? As an HCI + human-centered AI + education researcher, I am committed to addressing the critical challenge of education inequality. As the advancement of interactive AI systems reaches an inflection point, I am hopeful that AI can make personalized education more accessible and efficient. However, if these systems are not developed using a human-centered approach, they can fail to reach their full potential, cause harm, and even widen learning disparities. Therefore, I aim to enhance education access by creating human-centered interactive AI educational systems that enhance learning, respect user preferences, and ensure fairness.

Research Topics
I plan to work towards my research vision by tackling two fundamental questions.

First, since interactive AI educational systems are imperfect, opaque, and susceptible to bias, I ask: “How should they be deployed?” I conduct algorithmic impact assessments on existing and emerging systems. Currently, I am (1) evaluating the learning impact of AI errors generated by NLP-driven educational systems in STEM, and (2) identifying and addressing attitudinal and perceptual challenges with imperfect and opaque AI educational systems.

Second, for learning contexts that are yet hard to scale effectively due to a need for personalization, I ask: “How can interactive AI systems scale personalization?” I create novel interactive AI educational systems using a human-centered approach to tackle this. So far, I have worked in the context of spatial visualization training, and open-ended courses in non-STEM education.

Other Research Topics
I have worked on a broader set of HCI topics, including voting, conversational agents, and social network analysis.