About InspAIre
InspAIre is an interdisciplinary research group focused on the frontier of Human-AI and Multi-agent Collaboration. We bring together researchers and practitioners from various domains such as computer and information science, education, psychology, and human-computer interaction, to explore how humans and intelligent systems (not limited to LLMs) can effectively and efficiently learn from each other, and discover together.
We are committed to open science principles, with the aim of enhancing human potential (both kids and adults) and improving the accessibility, reliability, and explainability of human-centered AI. Our research topics focus on real-world challenges in education, scientific discovery, creative work, and professional knowledge domains where human-AI collaboration can unlock new possibilities.
Research Areas
Learning
Developing intelligent systems that can both learn from and teach humans, creating interactive environments to support knowledge and skill acquisition.
Exploration
Investigating how artificial intelligence enhances human imagination, creativity, and curiosity, and facilitates identifying novel directions and opportunities.
Discovery
Advancing science discovery through synergistic human-AI collaboration, where AI meets human intuition to unlock new insights across various domains.
Selected Works and Publications
The Imperfect Learner: Incorporating Developmental Trajectories in Memory-based Student Simulation
Zhengyuan Liu, Stella Xin Yin, Bryan Chen Zhengyu Tan, Roy Ka-Wei Lee, Guimei Liu, Dion Hoe-Lian Goh, Wenya Wang, Nancy F Chen. [Paper]
COGENT: A Curriculum-oriented Framework for Generating Grade-appropriate Educational Content
Zhengyuan Liu, Stella Xin Yin, Dion Hoe-Lian Goh, Nancy F. Chen. In Proceedings of BEA 2025. [Paper]
SingaKids: A Multilingual Multimodal Dialogic Tutor for Language Learning
Zhengyuan Liu, Geyu Lin, Hui Li Tan, Huayun Zhang, Yanfeng Lu, Xiaoxue Gao, Stella Xin Yin, He Sun, Hock Huan Goh, Lung Hsiang Wong, Nancy F. Chen. In Proceedings of ACL 2025. [Paper]
Scaffolding Language Learning via Multi-modal Tutoring Systems with Pedagogical Instructions
Zhengyuan Liu, Stella Xin Yin, Carolyn Lee, Nancy F. Chen. In Proceedings of IEEE CAI 2024. [Paper]
Personality-aware Student Simulation for Conversational Intelligent Tutoring Systems
Zhengyuan Liu, Stella Xin Yin, Geyu Lin, Nancy F. Chen. In Proceedings of EMNLP 2024. [Paper]
Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing
Fangkai Jiao, Chengwei Qin, Zhengyuan Liu, Nancy F. Chen, Shafiq Joty. In Proceedings of EMNLP 2024 (🏅Outstanding Paper Award). [Paper]
Understanding Determinants of Student Behavioral Intention in Singapore's AI Education: Insights from the Situated Expectancy-Value Theory
Stella Xin Yin, Dion Hoe-Lian Goh. Journal of Interactive Learning Environments, 2025. [Paper]
Scaling Up Collaborative Dialogue Analysis: An AI-driven Approach to Understanding Dialogue Patterns in Computational Thinking Education
Stella Xin Yin, Zhengyuan Liu, Dion Hoe-Lian Goh, Choon Lang Quek, Nancy F. Chen. In Proceedings of Learning Analytics & Knowledge 2025. [Paper]
Collaborative Learning in K-12 Computational Thinking Education: A Systematic Review
Stella Xin Yin, Dion Hoe-Lian Goh, Choon Lang Quek. Journal of Educational Computing Research, 2024. [Paper]
People
Our interdisciplinary research brings together experts from diverse backgrounds:
Zhengyuan Liu
Conversational AI,
Multi-modal LLMs, AI for Science
Stella Xin Yin
Collaborative Learning,
Computational Thinking
Dion Hoe-Lian Goh
Information Seeking Behavior,
Game-based Learning
Nancy F. Chen
Multi-modal Generative AI
AI for Healthcare and Education
Contact Us
We're always open to collaborations, contributions, and research partnerships and discussions about InspAIre. If you're interested in exploring various opportunities, please get in touch.
Email: zhengyua001@e.ntu.edu.sg, stellayin06@outlook.com