• Multifactorial and Multimodal Approaches for Advancing Forensic Age Estimation

    Published on September 3, 2025

    THE EVENT

    This online event examines current research on the use of machine learning and artificial intelligence  in forensic anthropology, with a particular focus on age estimation in both age-at-death analysis and legal age assessment. 

    Special attention will be given to deep learning approaches that combine skeletal, dental, and medical imaging data in order to improve the accuracy and reliability of age determination. The talk will review the state of the art in vision-based models and other computational methods, while also addressing major challenges in the field, including the scarcity of large, well-annotated datasets, the need for trustworthy and robust algorithms, and the critical issue of interpretability in forensic applications. 

    Furthermore, the presentation will highlight significant outcomes and ongoing research lines from two EU-funded projects — UMAFAE (Grant ID 101026482) and M2IbAE (Grant ID 101209534) coordinated by Panacea Cooperative Research. These initiatives underscore the importance of multifactorial and multimodal approaches for advancing forensic age estimation.

    The event was recorded on Thursday, Sep 18, 2025 at 16:00 CET. 

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    THE SPEAKERS

    David Navega is a forensic anthropologist and postdoctoral researcher at Panacea Cooperative Research, specializing in the application of machine learning and artificial intelligence to age estimation. He is currently working on M2IbAE (Multimodal and Multifactorial Image-based Age Estimation), a research project funded by the European Union within the framework of the Marie Skłodowska-Curie Actions.

    Javier Venema is a computer scientist and artificial intelligence researcher at Panacea Cooperative Research. He is currently developing a Ph.D. thesis focused on biological profile estimation using Artificial Intelligence.