AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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Here you can find the complete list of our 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
Sajiukumar, A.; Ranjan, A.; Parvathi, P. K.; Satheesh, A.; Udayan, J. Divya; Subramaniam, U.
Generative AI-Enabled Virtual Twin for Meeting Assistants Proceedings Article
In: T., Saba; A., Rehman (Ed.): Proc. - Int. Women Data Sci. Conf. at Prince Sultan Univ., WiDS-PSU, pp. 60–65, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 979-833152092-2 (ISBN).
Abstract | Links | BibTeX | Tags: 3D avatar generation, 3D Avatars, 3D reconstruction, AI-augmented interaction, Augmented Reality, Communication and collaborations, Conversational AI, Neural radiation field, neural radiation fields (NeRF), Radiation field, Real time performance, real-time performance, Three dimensional computer graphics, Virtual spaces, Voice cloning
@inproceedings{sajiukumar_generative_2025,
title = {Generative AI-Enabled Virtual Twin for Meeting Assistants},
author = {A. Sajiukumar and A. Ranjan and P. K. Parvathi and A. Satheesh and J. Divya Udayan and U. Subramaniam},
editor = {Saba T. and Rehman A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105007691247&doi=10.1109%2fWiDS-PSU64963.2025.00025&partnerID=40&md5=f0bfb74a8f854c427054c73582909185},
doi = {10.1109/WiDS-PSU64963.2025.00025},
isbn = {979-833152092-2 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Proc. - Int. Women Data Sci. Conf. at Prince Sultan Univ., WiDS-PSU},
pages = {60–65},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The growing dependence on virtual spaces for communication and collaboration has transformed interactions in numerous industries, ranging from professional meetings to education, entertainment, and healthcare. Despite the advancement of AI technologies such as three-dimensional modeling, voice cloning, and conversational AI, the convergence of these technologies in a single platform is still challenging. This paper introduces a unified framework that brings together state-of-the-art 3D avatar generation, real-time voice cloning, and conversational AI to enhance virtual interactions. The system utilizes Triplane neural representations and neural radiation fields (NeRF) for high-fidelity 3D avatar generation, speaker encoders coupled with Tacotron 2 and WaveRNN for natural voice cloning, and a context-aware chat algorithm for adaptive conversations. By overcoming the challenges of customization, integration, and real-time performance, the proposed framework addresses the increasing needs for realistic virtual representations, setting new benchmarks for AI-augmented interaction in virtual conferences, online representation, education, and healthcare. © 2025 IEEE.},
keywords = {3D avatar generation, 3D Avatars, 3D reconstruction, AI-augmented interaction, Augmented Reality, Communication and collaborations, Conversational AI, Neural radiation field, neural radiation fields (NeRF), Radiation field, Real time performance, real-time performance, Three dimensional computer graphics, Virtual spaces, Voice cloning},
pubstate = {published},
tppubtype = {inproceedings}
}
The growing dependence on virtual spaces for communication and collaboration has transformed interactions in numerous industries, ranging from professional meetings to education, entertainment, and healthcare. Despite the advancement of AI technologies such as three-dimensional modeling, voice cloning, and conversational AI, the convergence of these technologies in a single platform is still challenging. This paper introduces a unified framework that brings together state-of-the-art 3D avatar generation, real-time voice cloning, and conversational AI to enhance virtual interactions. The system utilizes Triplane neural representations and neural radiation fields (NeRF) for high-fidelity 3D avatar generation, speaker encoders coupled with Tacotron 2 and WaveRNN for natural voice cloning, and a context-aware chat algorithm for adaptive conversations. By overcoming the challenges of customization, integration, and real-time performance, the proposed framework addresses the increasing needs for realistic virtual representations, setting new benchmarks for AI-augmented interaction in virtual conferences, online representation, education, and healthcare. © 2025 IEEE.
Sabir, A.; Hussain, R.; Pedro, A.; Park, C.
Personalized construction safety training system using conversational AI in virtual reality Journal Article
In: Automation in Construction, vol. 175, 2025, ISSN: 09265805 (ISSN).
Abstract | Links | BibTeX | Tags: Construction safety, Construction safety training, Conversational AI, Digital elevation model, Helmet mounted displays, Language Model, Large language model, large language models, Personalized safety training, Personnel training, Safety training, Training Systems, Virtual environments, Virtual Reality, Workers'
@article{sabir_personalized_2025,
title = {Personalized construction safety training system using conversational AI in virtual reality},
author = {A. Sabir and R. Hussain and A. Pedro and C. Park},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002741042&doi=10.1016%2fj.autcon.2025.106207&partnerID=40&md5=376284339bf10fd5d799cc56c6643d36},
doi = {10.1016/j.autcon.2025.106207},
issn = {09265805 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Automation in Construction},
volume = {175},
abstract = {Training workers in safety protocols is crucial for mitigating job site hazards, yet traditional methods often fall short. This paper explores integrating virtual reality (VR) and large language models (LLMs) into iSafeTrainer, an AI-powered safety training system. The system allows trainees to engage with trade-specific content tailored to their expertise level in a third-person perspective in a non-immersive desktop virtual environment, eliminating the need for head-mounted displays. An experimental study evaluated the system through qualitative, survey-based assessments, focusing on user satisfaction, experience, engagement, guidance, and confidence. Results showed high satisfaction rates (>85 %) among novice users, with improved safety knowledge. Expert users suggested advanced scenarios, highlighting the system's potential for expansion. The modular architecture supports customization across various construction settings, ensuring adaptability for future improvements. © 2024},
keywords = {Construction safety, Construction safety training, Conversational AI, Digital elevation model, Helmet mounted displays, Language Model, Large language model, large language models, Personalized safety training, Personnel training, Safety training, Training Systems, Virtual environments, Virtual Reality, Workers'},
pubstate = {published},
tppubtype = {article}
}
Training workers in safety protocols is crucial for mitigating job site hazards, yet traditional methods often fall short. This paper explores integrating virtual reality (VR) and large language models (LLMs) into iSafeTrainer, an AI-powered safety training system. The system allows trainees to engage with trade-specific content tailored to their expertise level in a third-person perspective in a non-immersive desktop virtual environment, eliminating the need for head-mounted displays. An experimental study evaluated the system through qualitative, survey-based assessments, focusing on user satisfaction, experience, engagement, guidance, and confidence. Results showed high satisfaction rates (>85 %) among novice users, with improved safety knowledge. Expert users suggested advanced scenarios, highlighting the system's potential for expansion. The modular architecture supports customization across various construction settings, ensuring adaptability for future improvements. © 2024
2024
Kumaar, D. Prasanna; Abisha, D.; Christy, J. Ida; Evanjalin, R. Navedha; Rajesh, P.; Haris, K. Mohamed
WRISTVIEW: Augmented Reality and Generative AI Integration for Enhanced Online Shopping Experiences Proceedings Article
In: Int. Conf. I-SMAC (IoT Soc., Mob., Anal. Cloud), I-SMAC - Proc., pp. 1115–1120, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835037642-5 (ISBN).
Abstract | Links | BibTeX | Tags: Augmented Reality, Chatbots, Conversational AI, Customer satisfaction, Decision making, E-commerce Innovation, Growing demand, Immersive, Interactivity, Online shopping, Personalizations, Personalized Shopping Experience, Purchasing, Sales, Virtual environments, Virtual Try-On
@inproceedings{prasanna_kumaar_wristview_2024,
title = {WRISTVIEW: Augmented Reality and Generative AI Integration for Enhanced Online Shopping Experiences},
author = {D. Prasanna Kumaar and D. Abisha and J. Ida Christy and R. Navedha Evanjalin and P. Rajesh and K. Mohamed Haris},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208587489&doi=10.1109%2fI-SMAC61858.2024.10714789&partnerID=40&md5=e7742c8808cb551b17efe9ac3efeb961},
doi = {10.1109/I-SMAC61858.2024.10714789},
isbn = {979-835037642-5 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Int. Conf. I-SMAC (IoT Soc., Mob., Anal. Cloud), I-SMAC - Proc.},
pages = {1115–1120},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The traditional retail experience for purchasing watches lacks the interactivity and personalization that modern consumers seek. With the increasing shift towards online shopping platforms, there is a growing demand for an engaging and immersive virtual experience that allows customers to explore and try on watches. The absence of expert guidance during the online shopping process often results in less informed decision-making. To address these challenges, WRISTVIEW presents an innovative solution that integrates augmented reality (AR) and a conversational Generative AI (GENAI) chatbot. The AR component enables users to virtually try on watches, providing a realistic and interactive experience. The GENAI chatbot enhances this experience by offering expert advice, answering queries, and guiding users through the watch shopping journey, thereby creating a more personalized and informative shopping process. The objective of this research is to bridge the gap between the traditional in-store watch shopping experience and the online environment, ensuring that customers can make well-informed and satisfying purchase decisions in a virtual setting. The development, implementation, and potential impact of combining AR and GENAI technologies to transform the online watch shopping experience are discussed. © 2024 IEEE.},
keywords = {Augmented Reality, Chatbots, Conversational AI, Customer satisfaction, Decision making, E-commerce Innovation, Growing demand, Immersive, Interactivity, Online shopping, Personalizations, Personalized Shopping Experience, Purchasing, Sales, Virtual environments, Virtual Try-On},
pubstate = {published},
tppubtype = {inproceedings}
}
The traditional retail experience for purchasing watches lacks the interactivity and personalization that modern consumers seek. With the increasing shift towards online shopping platforms, there is a growing demand for an engaging and immersive virtual experience that allows customers to explore and try on watches. The absence of expert guidance during the online shopping process often results in less informed decision-making. To address these challenges, WRISTVIEW presents an innovative solution that integrates augmented reality (AR) and a conversational Generative AI (GENAI) chatbot. The AR component enables users to virtually try on watches, providing a realistic and interactive experience. The GENAI chatbot enhances this experience by offering expert advice, answering queries, and guiding users through the watch shopping journey, thereby creating a more personalized and informative shopping process. The objective of this research is to bridge the gap between the traditional in-store watch shopping experience and the online environment, ensuring that customers can make well-informed and satisfying purchase decisions in a virtual setting. The development, implementation, and potential impact of combining AR and GENAI technologies to transform the online watch shopping experience are discussed. © 2024 IEEE.