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I am a fourth-year Ph.D. candidate in the Academy of Interdisciplinary Studies at The Hong Kong University of Science and Technology (HKUST), advised by Prof. Fan Mingming and Prof. Qu Huamin. My current research focuses on developing and applying computational methods—such as cognitive modeling and machine learning—to understand and enhance human adaptive learning behaviors.
My work advances adaptive learning systems in two key directions: (1) leveraging human-centered design and emerging technologies—such as augmented reality (AR)—to create interactive support mechanisms that provide multi-modal, context-aware assistance, and (2) applying cognitive science and machine learning to differentiate cognitive load types and model trial-and-error learning strategies through reinforcement learning, enabling systems to provide human-like adaptive assistance. By integrating cognitive modeling, machine learning, and interactive system design, I aim to bridge the gap between theoretical insights and practical applications, creating technologies that adapt seamlessly to users’ cognitive states and learning needs. Beyond my core research, I am actively involved in AI-assisted healthcare, large language model (LLM)-supported accessibility for blind and low-vision (BLV) users, and the intersection of AI with computational media arts.
Currently, I am a visiting Ph.D. student at Prof. Antti Oulasvirta’s Computational Behavior Lab at Aalto University, Finland. Prior to this, I have been worked as a machine learning engienner in Baidu and deep learning researcher in Deepir, led by Prof. Steven Hoi. My work is driven by a passion for leveraging AI to uncover human nature and address pressing social challenges and contribute to a healthier, more inclusive society.
If my research interests align with yours or you’d like to collaborate, feel free to reach out via email! I am actively seeking academic or industry research positions!
