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 expand the Abstract, Links and BibTex record for each paper.
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
Michael, R.; Kutza, J. -O.; Werth, P.; Liebe, J. -D.; Schöning, J.
Simulating Vulnerability: An Examination of Ethical, Legal and Social Aspects in the Context of Training Child Protection Workers Proceedings Article
In: Cheong, M.; Herkert, J.; Zhu, Q.; Love, H. A. (Ed.): Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 9798331532284 (ISBN).
Abstract | Links | BibTeX | Tags: and social aspect), Artificial intelligence, artificial intelligence (AI), Case files, Child Protection, Child protections, Ethical, Ethical aspects, Information Management, Language Model, Large language model, large language model (LLM), Laws and legislation, Legal, Personnel training, Social aspect (ethical, Social aspects, Social Aspects (ELSA), Virtual Reality, Virtual Reality (VR) Training, Virtual reality training, Workers'
@inproceedings{michael_simulating_2025,
title = {Simulating Vulnerability: An Examination of Ethical, Legal and Social Aspects in the Context of Training Child Protection Workers},
author = {R. Michael and J. -O. Kutza and P. Werth and J. -D. Liebe and J. Schöning},
editor = {M. Cheong and J. Herkert and Q. Zhu and H. A. Love},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105014522871&doi=10.1109%2FETHICS65148.2025.11098302&partnerID=40&md5=c5cba2cca188ceb263701952c2f386ea},
doi = {10.1109/ETHICS65148.2025.11098302},
isbn = {9798331532284 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The success of artificial intelligence (AI), particularly large language models (LLMs), has led to innovative applications and numerous attempts to find a use for this tool in different fields. One of these fields is in the work fielded by child protection offices. The AId4Children project investigates the use of AI-generated virtual reality (VR) training environments for child protection workers. This VR training application simulates home visits and is generated on synthetically constructed cases of child abuse and neglect that are based on real case files. Using real case files for AI-based generation of VR training raises several ethical, legal, and social aspects (ELSA) and questions. One question Q1) is how to acquire and create an open data set on child endangerment case files. A second question Q2) is how to represent the vulnerable characters in VR respectfully. A third question Q3) is if the use of AI, incl. LLM within the context of child abuse and neglect is acceptable at all. This paper will discuss and provide the first answers to the considerations on ELSA raised by the explorative concept development of this VR training application. © 2025 Elsevier B.V., All rights reserved.},
keywords = {and social aspect), Artificial intelligence, artificial intelligence (AI), Case files, Child Protection, Child protections, Ethical, Ethical aspects, Information Management, Language Model, Large language model, large language model (LLM), Laws and legislation, Legal, Personnel training, Social aspect (ethical, Social aspects, Social Aspects (ELSA), Virtual Reality, Virtual Reality (VR) Training, Virtual reality training, Workers'},
pubstate = {published},
tppubtype = {inproceedings}
}
The success of artificial intelligence (AI), particularly large language models (LLMs), has led to innovative applications and numerous attempts to find a use for this tool in different fields. One of these fields is in the work fielded by child protection offices. The AId4Children project investigates the use of AI-generated virtual reality (VR) training environments for child protection workers. This VR training application simulates home visits and is generated on synthetically constructed cases of child abuse and neglect that are based on real case files. Using real case files for AI-based generation of VR training raises several ethical, legal, and social aspects (ELSA) and questions. One question Q1) is how to acquire and create an open data set on child endangerment case files. A second question Q2) is how to represent the vulnerable characters in VR respectfully. A third question Q3) is if the use of AI, incl. LLM within the context of child abuse and neglect is acceptable at all. This paper will discuss and provide the first answers to the considerations on ELSA raised by the explorative concept development of this VR training application. © 2025 Elsevier B.V., All rights reserved.
2024
Pooryousef, V.; Cordeil, M.; Besançon, L.; Bassed, R.; Dwyer, T.
Collaborative Forensic Autopsy Documentation and Supervised Report Generation using a Hybrid Mixed-Reality Environment and Generative AI Journal Article
In: IEEE Transactions on Visualization and Computer Graphics, vol. 30, no. 11, pp. 7452–7462, 2024, ISSN: 10772626 (ISSN), (Publisher: IEEE Computer Society).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Augmented Reality, Autopsy, Causes of death, Complex procedure, Computer graphics, computer interface, Data visualization, Digital forensics, Documentation, Forensic autopsy, Forensic engineering, Forensic investigation, forensic science, Forensic Sciences, Generative AI, human, Humans, Imaging, Information Management, Laws and legislation, Mixed reality, Mixed-reality environment, Post mortem imaging, procedures, Report generation, Three-Dimensional, three-dimensional imaging, User-Computer Interface, Visualization, Workflow
@article{pooryousef_collaborative_2024,
title = {Collaborative Forensic Autopsy Documentation and Supervised Report Generation using a Hybrid Mixed-Reality Environment and Generative AI},
author = {V. Pooryousef and M. Cordeil and L. Besançon and R. Bassed and T. Dwyer},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204066202&doi=10.1109%2FTVCG.2024.3456212&partnerID=40&md5=779bb563a50d94f358d9e94dd38a0c84},
doi = {10.1109/TVCG.2024.3456212},
issn = {10772626 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {IEEE Transactions on Visualization and Computer Graphics},
volume = {30},
number = {11},
pages = {7452–7462},
abstract = {—Forensic investigation is a complex procedure involving experts working together to establish cause of death and report findings to legal authorities. While new technologies are being developed to provide better post-mortem imaging capabilities—including mixed-reality (MR) tools to support 3D visualisation of such data—these tools do not integrate seamlessly into their existing collaborative workflow and report authoring process, requiring extra steps, e.g. to extract imagery from the MR tool and combine with physical autopsy findings for inclusion in the report. Therefore, in this work we design and evaluate a new forensic autopsy report generation workflow and present a novel documentation system using hybrid mixed-reality approaches to integrate visualisation, voice and hand interaction, as well as collaboration and procedure recording. Our preliminary findings indicate that this approach has the potential to improve data management, aid reviewability, and thus, achieve more robust standards. Further, it potentially streamlines report generation and minimise dependency on external tools and assistance, reducing autopsy time and related costs. This system also offers significant potential for education. A free copy of this paper and all supplemental materials are available at https://osf.io/ygfzx. © 2024 Elsevier B.V., All rights reserved.},
note = {Publisher: IEEE Computer Society},
keywords = {Artificial intelligence, Augmented Reality, Autopsy, Causes of death, Complex procedure, Computer graphics, computer interface, Data visualization, Digital forensics, Documentation, Forensic autopsy, Forensic engineering, Forensic investigation, forensic science, Forensic Sciences, Generative AI, human, Humans, Imaging, Information Management, Laws and legislation, Mixed reality, Mixed-reality environment, Post mortem imaging, procedures, Report generation, Three-Dimensional, three-dimensional imaging, User-Computer Interface, Visualization, Workflow},
pubstate = {published},
tppubtype = {article}
}
—Forensic investigation is a complex procedure involving experts working together to establish cause of death and report findings to legal authorities. While new technologies are being developed to provide better post-mortem imaging capabilities—including mixed-reality (MR) tools to support 3D visualisation of such data—these tools do not integrate seamlessly into their existing collaborative workflow and report authoring process, requiring extra steps, e.g. to extract imagery from the MR tool and combine with physical autopsy findings for inclusion in the report. Therefore, in this work we design and evaluate a new forensic autopsy report generation workflow and present a novel documentation system using hybrid mixed-reality approaches to integrate visualisation, voice and hand interaction, as well as collaboration and procedure recording. Our preliminary findings indicate that this approach has the potential to improve data management, aid reviewability, and thus, achieve more robust standards. Further, it potentially streamlines report generation and minimise dependency on external tools and assistance, reducing autopsy time and related costs. This system also offers significant potential for education. A free copy of this paper and all supplemental materials are available at https://osf.io/ygfzx. © 2024 Elsevier B.V., All rights reserved.