Homepage - Wei Ai

I am an Assistant Professor in the College of Information (INFO) and the Institute for Advanced Computer Studies (UMIACS) at the University of Maryland, College Park. I am a member of the CLIP Lab.

My research develops end-to-end data science solutions that combine machine learning, causal inference, and field experiments. My current research focuses on using AI to identify, measure, and promote effective teaching practices in K-12 education. This research builds on my broader work studying how social identity and non-verbal cues promote and facilitate collaboration and participation in virtual workspaces and online platforms.

I received my Ph.D. from the School of Information at University of Michigan. I was fortunate to be advised by Prof. Qiaozhu Mei and be a member of the Foreseer Group. Here is my CV.

Prospective Students:

We have funding available for multiple PhD students. I am able to mentor doctoral students through both the College of Information and the Department of Computer Science. If you are interested in working with me, please apply to either program and mention my name in your statement so that your application can be routed for my review. While I welcome inquiries, I find research statements and recommendation letters valuable in evaluating fit, so I prefer to review complete application packages. Feel free to email me after submitting your application.

I'm also happy to work with masters and undergraduate students at UMD. If you are interested in research opportunities, please send me an email with your CV and transcript. While I try to respond to all messages, I may not be able to reply to every inquiry due to the volume of emails.

Updates

We are launching the Center for Educational Data Science and Innovation (EDSI) and host the AI + Learning Symposium 2025. Join us for a one-day symposium exploring how AI research and innovations can help enhance educational experiences for all learners.
We received a Gates Foundation/Walton Family Foundation award on Building a High-Quality Benchmark Dataset of mathematics Classrooms to Accelerate Research in AI and Education, with PI Jing Liu. We are creating an open-source, high-quality multimodal dataset using multiple types of information from mathematics classrooms to facilitate the creation of cutting-edge AI models and automated tools for education researchers and practitioners.
In the News: UMD Today
We received an NSF Grant on Integration of Computer-Assisted Methods and Human Interactions to Understand Lesson Plan Quality and Teaching to Advance Middle-Grade Mathematics Instruction, with PI Min Sun and other Co-PIs. The project will leverage machine learning to assess mathematics lesson plan quality in the middle grades.
In the News: UMD Today
We received an UMD Grand Challenges Grant on Using Machine Learning to Measure and Improve Equity in K-12 Mathematics Classrooms, with PI Jing Liu and Co-PI Carol Espy-Wilson. We are building the M-Powering Teachers tool (M stands for machine) that utilizes NLP to analyze verbal classroom interactions and subsequently provides formative feedback to teachers.
In the News: UMIACS

Updates

Selected Recent Publications