My 16 friends from the University of Zaragoza and I have written a wonderful (and successful!) story for children to learn about our lives as women engineers. You can find more information and purchase the book at Unizar press or Amazon.
I feel extremely honoured to be the scientific side of the SciArt project SYNOCENE conceived by outstanding artists Marina Wainer and Sam Nester, and also in collaboration with my colleague Lucía Iglesias from European Commission’s DG Environment. SYNOCENE is a 360 degree involving sound installation where the voices of humans, artificial intelligence and nature co-exist exploring a decentered view of our anthropocentric experience of the natural world.
I was lucky to collaborate with the wonderful artist Max de Esteban on his brilliant work entitled A Forest, which is part of the permanent collection of the Museum of Contemporary Art of Barcelona (MACBA). In the artwork below, the artist politely asks a deep neural network for a selfie, even though -as an algorithm- it has no self. Will explainable AI help to bridge this gap between machines and human beings?
Published in IEEE Int. Conf. on Automatic Face and Gesture Recognition (FG 2019), 2019
In this paper we present DemogPairs, a publicly released validation dataset with 10.8K facial images and 58.3M identity verification pairs, distributed in demographically-balanced folds of Asian, Black and White females and males. DemogPairs and its associated benchmarking protocol are conceived to explore demographic biases and the cross-demographic behaviour of face recognition algorithms. More information on how to obtain DemogPairs here.
Citation: Hupont, I. and Fernández, C., DemogPairs: quantifying the impact of demographic imbalance in deep face recognition, 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019). IEEE, 2019. https://ieeexplore.ieee.org/abstract/document/8756625
Published in Nature Scientific Reports, 2022
This article presents the landscape of facial processing tasks, systems and applications. It identifies the 60 most relevant applications adopted for real-world uses, which are analysed under the lens of the European AI Act proposal and the 7 requirements for Trustworthy AI defined by the European High Level Expert Group on AI. It also reflects on current research, technical and societal challenges towards trustworthy facial processing systems.
Citation: Hupont Torres, I., Tolan, S., Gunes, H. and Gomez Gutierrez, E., The landscape of facial processing applications in the context of the European AI Act and the development of trustworthy systems, Nature Scientific Reports, ISSN 2045-2322, 12(1), 2022. https://www.nature.com/articles/s41598-022-14981-6
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I presented the first year of the DivinAI project at the AAAI-AIDBEI workshop.
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I was invited to give the closing keynote at TECNOSOCIAL 2022.
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I presented HUMAINT’s work on trustworthy AI as a part of the cycle of conferences on innovation management organised by the University of Zaragoza.
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I was happy to participate as a panelist in the METAVERSE LEGALTECH TOMORROW webinar organised by the Global LegalTech Hub.
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Honoured to participate in the roundtable on AI AND DEMOCRACY organised by Science for Democracy.
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It was my pleasure to talk about neural networks and trustworthy AI at SIE 2022, a reference annual innovation and entrepreneurship fair in Spain.
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Digital Future Society (DFS) invited face recognition companies, organisations and professionals to participate in a hackathon challenge consisting on adapting their products to the new Artificial Intelligence regulation proposal in the European Union (AI Act). They kindly invited me as a member of the jury, together with outstanding experts on data protection, digital regulation and AI.