Dr Mestre joined the University of Southampton in 2021 and is currently a New Frontiers Fellow in Machine Learning at the School of Electronics and Computer Science of the University of Southampton. Prior to this, he was a postdoctoral Research Fellow in the 'Rebooting Democracy' project at the Politics and International Relations Department. He's now the PI of the ESRC New Investigator award "A framework for research governance and application of bio-hybrid robotics", where he researches social, ethical and policy implications of emergent technologies using mixed research methods.
His research is interdisciplinary and lies at the interface of computer science 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's a member of the steering committee of the Centre for Democratic Futures (CDF), an Associate at the Digital Humanities (DH) hub of the University and a member of the Institute for Life Sciences (IfLS).
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. He published his research in journals like Science Robotics, Advanced Materials Technologies or Biofabrication, he submitted a patent and collaborated with private companies.
- Responsible Research and Innovation of emergent technologies
- Multimodal machine learning and Natural Language Processing
- Computational social science
- Bio-hybrid robotics
- Digital Humanities
Dr Mestre's current research very interdisciplinary in nature and ranges from computer science to political science. Some of his research efforts are 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 focuses 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.
He is interested in the ethical and social implications of emergent technologies, as well as their public co-governance and co-design. He's the PI of the ESRC New Investigator award "A framework for research, governance and application of bio-hybrid robotics", where he studies responsible research and innovation of this emergent technology, which was the focus of his PhD. He is also currently studying the biases and ethical aspects of novel artificial intelligence technologies like large language models (LLMs), and the social critiques around them.
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.
- Alan Turing's postdoctoral enrichment award (PDEA) (2022)