Tiffany Wu

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Welcome! đź‘‹

I am currently a Postdoctoral Fellow at Carnegie Mellon University’s Human-Computer Interaction Institute, where I work with Dr. Ken Koedinger and Dr. Danielle Thomas on the PLUS Project, a hybrid human-AI tutoring program that aims to reduce opportunity gaps in math education by combining the complementary strengths of human tutors and AI.

Broadly, my research weaves machine learning, AI, causal inference, and psychometric methods to design, evaluate, and scale PK-12 educational tools and interventions. My work to date has spanned three substantive areas: chronic absenteeism, early childhood education policy, and math education. I am deeply committed to leveraging advances in data science and AI to advance educational opportunity and equity. Through research-practice partnerships, I aim to produce research that is rigorous, accessible, and grounded in the lived experiences of students, families, and practitioners across diverse educational contexts.

My research has been deeply influenced by my work as a public high school teacher in Chicago and then as a research analyst for an education technology non-profit prior to starting my doctoral training.

I received my PhD in Education & Psychology along with a dual master’s degree in Statistics from the University of Michigan, where I was fortunate to be advised by Dr. Christina Weiland. During this time, I was an IES Causal Inference Predoctoral Fellow and an APPAM Equity and Diversity Fellow. I also hold a B.S. in Secondary Education & History from Northwestern University and an M.A. in Psychology from the University of Chicago.

Outside of work, I like to paint, play the piano, and play pickleball.

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