southampton

About

Dr Mestre joined the University of Southampton in 2021 and is currently a Lecturer at the School of Electronics and Computer Science of the University of Southampton and a Turing Fellow at the Alan Turing Institute. He's the PI of the ESRC New Investigator award "Biohybrid Futures: A framework for research governance and application of bio-hybrid robotics", where he researches social, ethical and policy implications of emergent technologies like biohybrid robotics using mixed research methods. He's also the PI of the RAI UK International Partnership grant "RAI4MH: Exploring Fairness and Bias of Multimodal Natural Language Processing for Mental Health" in collaboration with the Institute for Experiential AI @ Northeastern University (US) and PI of the upcoming £1.2M UKRI Cross-Research Council grant SOUNDSCALE, investigating the responsible development of distributed fibre optic sensing for smart cities through inter- and transdisciplinary research with the physical, computer and social sciences, arts and humanities, and engagement with citizens, policymakers, nonprofits and industry.

His research is interdisciplinary and focuses on the responsible development and socio-technical evaluation of emerging technologies, at the interface of disciplines like computer science, science and technology studies and political science. Much of his research efforts are focused on computational social science (and argumentation mining in particular) using multimodal machine learning methods (text-as-data, image-as-data, audio-as-data). He also studies digital tools for deliberation applied to democratic innovations; the ethics, social implications and governance of emergent technologies like natural language processing (NLP) and bio-hybrid robots; and the application of machine learning in digital humanities. He is co-director of the Centre for Democratic Futures (CDF), Ethics & Governance lead at the Centre for Robotics, Associate at the Digital Humanities (DH) hub of the University and a member of the Institute for Life Sciences (IfLS).

Prior to this, he was a New Frontiers Fellow in Machine Learning at the School of Electronics and Computer Science and before that a postdoctoral Research Fellow in the 'Rebooting Democracy' project at the Politics and International Relations Department. In the past, during his PhD defended in November 2020, he researched at the Institute for Bioengineering of Catalonia (IBEC) in the development of bio-hybrid robotics and nanorobotics, at the interface of fields like tissue engineering, biomedicine, material science, computer science, physics, 3D-bioprinting, robotics and computer vision.

Research

Research groups

Member of:

Research interests

Responsible Research and Innovation of emergent technologies
Multimodal machine learning and Natural Language Processing
Computational social science
Bio-hybrid robotics
Digital Humanities

Current research

Dr Mestre's current research very interdisciplinary in nature and lies at the interface of fields like computer science, science and technology studies, biohybrid robotics and political science. He is interested in the ethical and social implications of emergent technologies, as well as their public co-governance. As PI of the ESRC New Investigator award "Biohybrid Futures: A framework for research governance and application of bio-hybrid robotics", he studies responsible research and innovation of this emerging technology, which was the focus of his PhD. He is also currently studying the biases and ethical aspects of novel AI technologies like large language models (LLMs), as well as their responsible application in domains like mental health, through the RAI UK International Partnership grant RAI4MH: Exploring Fairness and Bias of Multimodal Natural Language Processing for Mental Health in collaboration with the Institute for Experiential AI @ Northeastern University (US). From January 2025, he will lead the £1.2M UKRI Cross-Research Council grant SOUNDSCALE project, investigating the responsible development of distributed fibre optic sensing for smart cities through inter- and transdisciplinaryr esearch with the physical, computer and social sciences, arts and humanities, and engagement with citizens, policymakers, nonprofits and industry.

Some of his research efforts have also focused on natural language processing (NLP) and multimodal machine learning, particularly applied, although not exclusively, to argumentation mining (the field of computer science that aims at extracting and analysing arguments from natural dialogue). In general, he has focused on the study and application of multimodal methodologies within the text-as-data, image-as-data and audio-as-data paradigms in political science research. His previous works have tackled the classification of arguments from presidential debates using audio-textual information, and he has developed datasets for this purpose.

He is also interested in the application of these multimodal machine learning techniques in computational social (political) science, from social media analysis to the study of public deliberation and parliamentary debates. He collaborates in the ‘Rebooting Democracy’ project, where he works in the development of digital tools for public deliberation based on argumentation maps and in the development of democratic innovations based on citizens’ assemblies or mini publics. He's worked in projects with impact for citizens and policy makers, such as the Southampton Climate Citizens' Assembly or public dialouges in collaboration with a UK Select Committee, where he led the digital/computational aspects, from collaborative argument mapping to topic modelling to inform citizens' perceptions.

Finally, his interdisciplinary research bridges to other fields, like biomedical engineering, environmental science or digital humanities. He works in projects detecting and classifying maritime events from distributed acoustic sensing (DAS) systems using multimodal machine learning in collaboration with the National Oceanography Institute (NOC). He is also PI of smaller projects in digital humanities around multimodal machine learning and interactivity in an immersive space and multimodal argumentation mining.