Xiaomeng Huang is a PhD candidate in Educational Communication and Technology at New York University. She holds an EdM in Technology, Innovation, and Education from Harvard University. Her research lies at the intersection of Artificial Intelligence in Education, Multimodal Learning Analytics, and Computer-Supported Collaborative Learning.
Xiaomeng studies how multimodal and explainable AI can support socially situated skill development in collaborative learning. Grounded in learning sciences, measurement theory, and dialogic pedagogy, she designs theory-informed learner models and pedagogical feedback systems that help students reflect on and improve skills such as active listening.
Her work has been published in leading venues including the Journal of Learning Analytics, International Conference of Artificial Intelligence in Education (AIED), International Conference of Computer-Supported Collaborative Learning (CSCL), and International Conference of Learning Analytics and Knowledge (LAK).