About
25
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Introduction
My primary research focuses on the Hci, affective computing, and interaction behaviors between humans and generative AI, especially large-scale language models like GPT. I am particularly interested in exploring how these technologies can be applied to benefit human workflows. Additionally, the ethical considerations surrounding generative AI are also one of the central topics of my research.
Current institution
Additional affiliations
April 2021 - August 2022
August 2022 - present
Education
August 2022 - August 2026
July 2020 - December 2022
February 2016 - August 2019
Publications
Publications (25)
Thematic analysis is a cornerstone of qualitative research, yet it is often marked by labor-intensive procedures. Recent advances in artificial intelligence (AI), especially with large-scale language models (LLMs) such as ChatGPT, present potential avenues to enhance qualitative data analysis. This research delves into the effectiveness of ChatGPT...
Community management is critical for stakeholders to collaboratively build and sustain communities with socio-technical support. However, most of the existing research has mainly focused on the community members and the platform, with little attention given to the developers who act as intermediaries between the platform and community members and d...
Understanding and recognizing emotions are important and challenging issues in the metaverse era. Understanding, identifying, and predicting fear, which is one of the fundamental human emotions , in virtual reality (VR) environments plays an essential role in immersive game development, scene development, and next-generation virtual human-computer...
Qualitative research, renowned for its in-depth exploration of complex phenomena, often involves time-intensive analysis, particularly during the coding stage. Existing software for qualitative evaluation frequently lacks automatic coding capabilities, user-friendliness, and cost-effectiveness. The advent of Large Language Models (LLMs) like GPT-3...
Assistive technologies for people with visual impairments (PVI) have made significant advancements, particularly with the integration of artificial intelligence (AI) and real-time sensor technologies. However, current solutions often require PVI to switch between multiple apps and tools for tasks like image recognition, navigation, and obstacle det...
Traditional image annotation tasks rely heavily on human effort for object selection and label assignment, making the process time-consuming and prone to decreased efficiency as annotators experience fatigue after extensive work. This paper introduces a novel framework that leverages the visual understanding capabilities of large multimodal models...
As immersive social platforms like VRChat increasingly adopt gen-erative AI (GenAI) technologies, it becomes critical to understand how community members perceive, negotiate, and utilize these tools. In this preliminary study, we conducted a qualitative analysis of VRChat-related Discord discussions, employing a deductive coding framework to identi...
Large multimodal models (LMMs) have enabled new AI-powered applications that help people with visual impairments (PVI) receive natural language descriptions of their surroundings through audible text. We investigated how this emerging paradigm of visual assistance transforms how PVI perform and manage their daily tasks. Moving beyond usability asse...
This study investigates the feasibility and performance of using large language models (LLMs) to automatically annotate human emotions in everyday scenarios. We conducted experiments on the DailyLife subset of the publicly available FERV39k dataset, employing the GPT-4o-mini model for rapid, zero-shot labeling of key frames extracted from video seg...
Virtual Reality (VR) has the capacity to offer unparalleled immersive experiences, particularly in the domain of horror gaming. However, creating both practical and enjoyable VR applications necessitates a nuanced understanding of user emotions and behaviors. To fill this gap, we conducted semi-structured interviews with 25 participants who engaged...
Generative AI has drawn significant attention from stakeholders in higher education. As it introduces new opportunities for personalized learning and tutoring support, it simultaneously poses challenges to academic integrity and leads to ethical issues. Consequently, governing responsible AI usage within higher education institutions (HEIs) becomes...
Generative AI has drawn significant attention from stakeholders in higher education. As it introduces new opportunities for personalized learning and tutoring support, it simultaneously poses challenges to academic integrity and leads to ethical issues. Consequently, governing responsible AI usage within higher education institutions (HEIs) becomes...
As Large-Scale Language Models (LLMs) continue to evolve, they demonstrate significant enhancements in performance and an expansion of functionalities, impacting various domains, including education. In this study, we conducted interviews with 14 students to explore their everyday interactions with ChatGPT. Our preliminary findings reveal that stud...
People with visual impairments perceive their environment non-visually and often use AI-powered assistive tools to obtain textual descriptions of visual information. Recent large vision-language model-based AI-powered tools like Be My AI are more capable of understanding users' inquiries in natural language and describing the scene in audible text;...
Content creators increasingly utilize generative artificial intelligence (Gen-AI) on platforms such as YouTube, TikTok, Instagram, and various blogging sites to produce imaginative images, AI-generated videos, and articles using Large Language Models (LLMs). Despite its growing popularity, there remains an underexplored area concerning the specific...
This preliminary study investigated user experiences in VR horror games, highlighting fear-triggering and gender-based differences in perception. By utilizing a scientifically validated and specially designed questionnaire, we successfully collected questionnaire data from 23 subjects for an early empirical study of fear induction in a virtual real...
Both sensor networks and data fusion are essential foundations for developing the smart home Internet of Things (IoT) and related fields. We proposed a multi-channel sensor network construction method involving hardware, acquisition, and synchronization in the smart home environment and a smart home data fusion method (SHDFM) for multi-modal data (...
In times of crisis, international travel becomes tenuous and anxiety provoking. The crisis informatics and Human-Computer Interaction (HCI) community has paid increasing attention to the use of Information and Communication Technologies (ICTs) in various crisis settings. However, little is known about the travelers' actual experiences in whole trip...
With the rapid development of artificial intelligence, the Internet of Things and big data, etc., the smart home enters the Era 3.0, which profoundly relies on user-based big data mining and deep learning. At present, smart interaction, intelligent perception, and complex decision-making in the smart home urgently need new supporting technologies a...
The COVID-19 pandemic led governments to rely on the versatility of social media to communicate with their citizens. This paper analyzes the Facebook communication of political leaders and health departments from 17 countries during the COVID-19 pandemic. We evaluate the citizen's response under the frameworks of media richness and user engagement....
