AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2025
Cao, J.; Zhou, M.; Wang, J.; Liu, G.; Niyato, D.; Mao, S.; Han, Z.; Kang, J.
A Unified Framework for Underwater Metaverse with Optical Perception Journal Article
In: IEEE Wireless Communications, vol. 32, no. 3, pp. 220–231, 2025, ISSN: 15361284 (ISSN), (Publisher: Institute of Electrical and Electronics Engineers Inc.).
Abstract | Links | BibTeX | Tags: AI Technologies, Deep sea exploration, Imaging technology, Marine conservations, Metaverses, Optical-, Quantum imaging, Underwater environments, Unified framework, Virtual reality system
@article{cao_unified_2025,
title = {A Unified Framework for Underwater Metaverse with Optical Perception},
author = {J. Cao and M. Zhou and J. Wang and G. Liu and D. Niyato and S. Mao and Z. Han and J. Kang},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105006878504&doi=10.1109%2FMWC.006.2400050&partnerID=40&md5=6091264c581faa5f1349483d889ebb3e},
doi = {10.1109/MWC.006.2400050},
issn = {15361284 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {IEEE Wireless Communications},
volume = {32},
number = {3},
pages = {220–231},
abstract = {With the advancement of AI technology and increasing attention to deep-sea exploration, the underwater Metaverse is gradually emerging. This article explores the concept of underwater Metaverse, emerging virtual reality systems, and services aimed at simulating and enhancing the virtual experience of marine environments. First, we discuss potential applications of underwater Metaverse in underwater scientific research and marine conservation. Next, we design the architecture and highlight the corresponding design requirements. Then, we present the characteristics of different underwater imaging technologies, such as underwater acoustic imaging, underwater radio imaging, and underwater quantum imaging, in the supporting technologies of the underwater Metaverse. Quantum imaging (QI) technology is suitable for extremely low-light underwater environments, improving the precision and efficiency of underwater imaging. Based on this, we present a use case for building a realistic underwater virtual world using underwater quantum imaging-generative artificial intelligence (QI-GenAI) technology. The results demonstrate the effectiveness of the underwater Metaverse framework in simulating complex underwater environments, thus validating its potential to provide high-quality, interactive underwater virtual experiences. Finally, the article examines important future research directions of underwater Metaverse and provides new perspectives for marine science and conservation. © 2025 Elsevier B.V., All rights reserved.},
note = {Publisher: Institute of Electrical and Electronics Engineers Inc.},
keywords = {AI Technologies, Deep sea exploration, Imaging technology, Marine conservations, Metaverses, Optical-, Quantum imaging, Underwater environments, Unified framework, Virtual reality system},
pubstate = {published},
tppubtype = {article}
}
With the advancement of AI technology and increasing attention to deep-sea exploration, the underwater Metaverse is gradually emerging. This article explores the concept of underwater Metaverse, emerging virtual reality systems, and services aimed at simulating and enhancing the virtual experience of marine environments. First, we discuss potential applications of underwater Metaverse in underwater scientific research and marine conservation. Next, we design the architecture and highlight the corresponding design requirements. Then, we present the characteristics of different underwater imaging technologies, such as underwater acoustic imaging, underwater radio imaging, and underwater quantum imaging, in the supporting technologies of the underwater Metaverse. Quantum imaging (QI) technology is suitable for extremely low-light underwater environments, improving the precision and efficiency of underwater imaging. Based on this, we present a use case for building a realistic underwater virtual world using underwater quantum imaging-generative artificial intelligence (QI-GenAI) technology. The results demonstrate the effectiveness of the underwater Metaverse framework in simulating complex underwater environments, thus validating its potential to provide high-quality, interactive underwater virtual experiences. Finally, the article examines important future research directions of underwater Metaverse and provides new perspectives for marine science and conservation. © 2025 Elsevier B.V., All rights reserved.
Chen, Y.; Yan, Y.; Yang, G.
Bringing Microbiology to Life in Museum: Using Mobile VR and LLM-Powered Virtual Character for Children's Science Learning Proceedings Article
In: Chui, K. T.; Jaikaeo, C.; Niramitranon, J.; Kaewmanee, W.; Ng, K. -K.; Ongkunaruk, P. (Ed.): pp. 83–87, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 9798331595500 (ISBN).
Abstract | Links | BibTeX | Tags: Computer aided instruction, E-Learning, Engineering education, Experimental groups, Immersive technologies, Informal learning, Language Model, Large language model, large language models, Learning systems, Microbiology, Mobile virtual reality, Museum, Museums, Science education, Science learning, Virtual addresses, Virtual character, Virtual Reality, Virtual reality system
@inproceedings{chen_bringing_2025,
title = {Bringing Microbiology to Life in Museum: Using Mobile VR and LLM-Powered Virtual Character for Children's Science Learning},
author = {Y. Chen and Y. Yan and G. Yang},
editor = {K. T. Chui and C. Jaikaeo and J. Niramitranon and W. Kaewmanee and K. -K. Ng and P. Ongkunaruk},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105015708152&doi=10.1109%2FISET65607.2025.00025&partnerID=40&md5=77ae9a4829656155010abc280a817a72},
doi = {10.1109/ISET65607.2025.00025},
isbn = {9798331595500 (ISBN)},
year = {2025},
date = {2025-01-01},
pages = {83–87},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Although the increasing advantages of immersive technology-enhanced museum informal learning in children's science education, the application of mobile virtual reality (MVR) technology combined with large language models (LLM) in this environment has not yet been fully explored. Furthermore, virtual character, as an intelligent learning assistant, is capable of providing personalized guidance and instant feedback to children through natural language interactions, but its potential in museum learning has yet to be fully tapped. To address these gaps, this study investigates the effectiveness of integrating MVR with LLM-powered virtual character in promoting children's microbiology learning during museum activities. In this paper, the technology-enhanced POE (Prediction-observation-explanation) learning model was studied, and the corresponding MVR system was designed and developed to carry out microbial learning activities. A quasiexperimental design was used with 60 children aged 10-12. The experimental group learned via an MVR system combining LLM-powered virtual character, while the control group used traditional methods. Results showed the experimental group significantly outperformed the control group in both academic achievement and learning motivation, including attention, confidence, and satisfaction. This provides evidence for using immersive technologies in informal learning and offers insights into applying LLM-powered virtual character in science education. © 2025 Elsevier B.V., All rights reserved.},
keywords = {Computer aided instruction, E-Learning, Engineering education, Experimental groups, Immersive technologies, Informal learning, Language Model, Large language model, large language models, Learning systems, Microbiology, Mobile virtual reality, Museum, Museums, Science education, Science learning, Virtual addresses, Virtual character, Virtual Reality, Virtual reality system},
pubstate = {published},
tppubtype = {inproceedings}
}
Although the increasing advantages of immersive technology-enhanced museum informal learning in children's science education, the application of mobile virtual reality (MVR) technology combined with large language models (LLM) in this environment has not yet been fully explored. Furthermore, virtual character, as an intelligent learning assistant, is capable of providing personalized guidance and instant feedback to children through natural language interactions, but its potential in museum learning has yet to be fully tapped. To address these gaps, this study investigates the effectiveness of integrating MVR with LLM-powered virtual character in promoting children's microbiology learning during museum activities. In this paper, the technology-enhanced POE (Prediction-observation-explanation) learning model was studied, and the corresponding MVR system was designed and developed to carry out microbial learning activities. A quasiexperimental design was used with 60 children aged 10-12. The experimental group learned via an MVR system combining LLM-powered virtual character, while the control group used traditional methods. Results showed the experimental group significantly outperformed the control group in both academic achievement and learning motivation, including attention, confidence, and satisfaction. This provides evidence for using immersive technologies in informal learning and offers insights into applying LLM-powered virtual character in science education. © 2025 Elsevier B.V., All rights reserved.
Ding, S.; Yalla, J. P.; Chen, Y.
Demo Abstract: RAG-Driven 3D Question Answering in Edge-Assisted Virtual Reality Proceedings Article
In: Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 9798331543709 (ISBN).
Abstract | Links | BibTeX | Tags: Edge computing, Edge server, Interface states, Knowledge database, Language Model, Local knowledge, Office environments, Question Answering, Real- time, User interaction, User interfaces, Virtual environments, Virtual Reality, Virtual reality system, Virtual-reality environment
@inproceedings{ding_demo_2025,
title = {Demo Abstract: RAG-Driven 3D Question Answering in Edge-Assisted Virtual Reality},
author = {S. Ding and J. P. Yalla and Y. Chen},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105017970015&doi=10.1109%2FINFOCOMWKSHPS65812.2025.11152992&partnerID=40&md5=0e079de018ae9c4a564b98c304a9ea6c},
doi = {10.1109/INFOCOMWKSHPS65812.2025.11152992},
isbn = {9798331543709 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The rapid development of large language models (LLMs) has created new opportunities in 3D question answering (3D-QA) for virtual reality (VR). 3D-QA enhances user interaction by answering questions about virtual environments. However, performing 3D-QA in VR systems using LLM-based approaches is computation-intensive. Furthermore, general LLMs tend to generate inaccurate responses as they lack context-specific information in VR environments. To mitigate these limitations, we propose OfficeVR-QA, a 3D-QA framework for edge-assisted VR to alleviate the resource constraints of VR devices with the help of edge servers, demonstrated in a virtual office environment. To improve the accuracy of the generated answers, the edge server of OfficeVR-QA hosts retrieval-augmented generation (RAG) that augments LLMs with external knowledge retrieved from a local knowledge database extracted from VR environments and users. During an interactive demo, OfficeVR-QA will continuously update the local knowledge database in real time by transmitting participants' position and orientation data to the edge server, enabling adaptive responses to changes in the participants' states. Participants will navigate a VR office environment, interact with a VR user interface to ask questions, and observe the accuracy of dynamic responses based on their real-time state changes. © 2025 Elsevier B.V., All rights reserved.},
keywords = {Edge computing, Edge server, Interface states, Knowledge database, Language Model, Local knowledge, Office environments, Question Answering, Real- time, User interaction, User interfaces, Virtual environments, Virtual Reality, Virtual reality system, Virtual-reality environment},
pubstate = {published},
tppubtype = {inproceedings}
}
The rapid development of large language models (LLMs) has created new opportunities in 3D question answering (3D-QA) for virtual reality (VR). 3D-QA enhances user interaction by answering questions about virtual environments. However, performing 3D-QA in VR systems using LLM-based approaches is computation-intensive. Furthermore, general LLMs tend to generate inaccurate responses as they lack context-specific information in VR environments. To mitigate these limitations, we propose OfficeVR-QA, a 3D-QA framework for edge-assisted VR to alleviate the resource constraints of VR devices with the help of edge servers, demonstrated in a virtual office environment. To improve the accuracy of the generated answers, the edge server of OfficeVR-QA hosts retrieval-augmented generation (RAG) that augments LLMs with external knowledge retrieved from a local knowledge database extracted from VR environments and users. During an interactive demo, OfficeVR-QA will continuously update the local knowledge database in real time by transmitting participants' position and orientation data to the edge server, enabling adaptive responses to changes in the participants' states. Participants will navigate a VR office environment, interact with a VR user interface to ask questions, and observe the accuracy of dynamic responses based on their real-time state changes. © 2025 Elsevier B.V., All rights reserved.