Enhancing Smartphone Eye Tracking with Cursor-Based Interactive Implicit Calibration
Hi, My name is Chang Liu 刘畅.
I am currently working as research assistant in Pervasive human computer Interaction Lab in Tsinghua University. I have earned a M.Eng. degree in Computer Science from Tsinghua University in July 2024.
My research interest focuses on understanding and leveraging the mutual influence between interaction contexts and user behavior. Specifically, user behavior in a given interaction context can implicitly reflect user’s intentions, strategies, preferences. Conversely, adjustments to the interaction context can potentially impact user behavior. I believe an ideal interaction system should learn from users' daily behaviors and dynamically update itself to enhance the interaction experience.
Specifically, I’m interested in pursuing research in the following areas:
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Exploring the impact of AI as an interaction context. Investigating how AI feedback influences users' behavioral and cognitive patterns.
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Developing sensing or interactive systems capable of sensing users' long-term physiological changes, such as myopia and muscle fatigue, or psychological changes, such as overstress or depression.
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Developing efficient multimodal interaction Systems, particularly about eye tracking, human-AI collaboration, or embodied intelligence.
Education
Zhejiang University | 09/2012 - 07/2016
Bachalor student, Major in Tea Science, Minor in Economics.
Pervasive Human Computer Interaction Laboratory, Tsinghua University | 09/2021 - 07/2024
Master student, Advisor: Prof. Chun Yu, Prof. Yuanchun Shi
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Led the project of CalibRead: Unobtrusive Eye Tracking Calibration from Natural Reading Behavior, where we propose an implicit calibration method for eye tracking device through natural reading behavior.
Employment
Zhuoshi Advertising Co., Ltd. | 08/2016 - 08/2021
3D Modeling, Visual Effect Artist, Designer, Video Editor
Pervasive Human Computer Interaction Laboratory, Tsinghua University | 08/2024 - now
Research Assistant
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Led the project of Enhancing Smartphone Eye Tracking with Cursor-Based Interactive ImplicitCalibration, where we proposed an continuous, implicit calibration method for eye tracking by introducing an cursor‑based interaction on smartphone.
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Co-authored the project of Detecting Overreliance on Conversational LLM from Interaction Behaviors, where we propose a method to detect the overreliance on Conversational Large Language Model using behavioral data during Interaction
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Co-authored the project of 3DRing: Enabling Low-Cost 3D Hand Position Tracking by Fusing Optical andInertial Sensing, where we propose a hand tracking method that fuses high frame rate data from a single IMU ring with adaptive, low frame rate optical data.