夜雨聆风
SEMINAR INFORMATION
Topic
Human-Centered AI: Designing Collaborative AI Systems for Learning, Reflection, and Creativity
Time
02:00-03:00 PM
Date
June 30th, 2026
Venue
Room 415, Teaching A
Zoom meeting
https://cuhk-edu-cn.zoom.us/j/3535854285?omn=94676400880
Meeting ID：3535854285
Speaker
Dr.YANG Kexin
(Carnegie Mellon University)
Host
Prof. ZHAO Zhanzhan
(The Chinese University of Hong Kong, Shenzhen)
ABOUT THE SPEAKER
Dr. YANG Kexin
Carnegie Mellon University
Dr. YANG Kexin received her Ph.D. in Human-Computer Interaction from the Human-Computer Interaction Institute, School of Computer Science, Carnegie Mellon University, and is currently a Postdoctoral Researcher at the University of Pennsylvania Graduate School of Education. Her research advances Human-AI collaboration by leveraging multimodal learning analytics (MMLA) and large language models (LLMs) to design, develop, and evaluate intelligent and human-centered AI systems. Her work has been published in leading venues including the ACM Conference on Human Factors in Computing Systems (CHI), ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), International Conference on Artificial Intelligence in Education (AIED), International Conference on Educational Data Mining (EDM), European Conference on Technology Enhanced Learning (EC-TEL), and the Journal of Computer Assisted Learning. Her research has received the Best Student Paper Award at EDM 2024 and the Best Design Paper Award at ISLS 2023, and has been supported by the National Science Foundation.
ABSTRACT
Artificial Intelligence is increasingly becoming a collaborative partner in education, work, and everyday life. However, designing these collaborative AI systems to effectively enhance human capabilities — while maintaining human agency — remains a fundamental challenge. This talk examines the design of human-centered AI systems across three interconnected contexts: learning, reflection, and creativity. Drawing on a series of projects spanning educational technology, generative AI, multimodal analytics, and creative-support tools, Dr. YANG demonstrates how carefully crafted AI interaction paradigms can augment cognitive and creative processes while keeping humans in meaningful control. The central question driving this research is: How can we design AI systems that enhance human learning and reflection while maintaining meaningful human control? Dr. YANG concludes by outlining future directions in Human-AI Collaboration, including AI agents and multimodal interaction, and discusses how these advances can inform the design of next-generation intelligent systems.
You are warmly welcome!
