Hello, I'm —

Jialing Wu

I am a Ph.D. student in Engineering Education (minor in Computer Science & Engineering, AI track) at The Ohio State University, advised by Dr. Adam Carberry. Before entering academia, I spent five years as a consultant in education sector, recruiting for international schools and K-12 organizations — work that gave me a front-row view of who gets access to quality education and who gets left behind. That question brought me to research.

My work centers on AI and computational methods across educational research, teaching practice, and student learning. I use and evaluate machine learning, LLMs, network analysis, GIS, and mixed-methods designs across engineering education and other educational contexts, with particular attention to equity and access.

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Be humble, be confident.

Education

The Ohio State University

Ph.D. Engineering Education · 2024–2028

Vanderbilt University

M.Ed. Intl. Education Policy · 2022–2024

Shanghai University

B.E. Mechanical Engineering · 2013–2017

GIS
Network Analysis
LPA / LCA
NLP · LLM
Machine Learning
Critical Quant
Pre-college Engineering
AI Policy
Equity & Access
Teaching Practice
Student Learning

Research

AI & Computational Methods for Research

Using and evaluating computational approaches to generate transparent and actionable educational knowledge.

→ methods

AI in Teaching Practice

Examining how teachers, curricula, policies, and professional learning shape meaningful AI integration.

→ teaching

AI & Student Learning

Studying how students understand, use, and learn with AI, including literacy, trust, identity, access, and outcomes.

→ learning