Artificial Intelligence for the Wellbeing and Sustainability of Societies

Dr. Villa started out as a Theoretical Ecologist and had a long parallel career as a Scientific Software Designer and Engineer. After carrying out research in many fields of Ecology, he worked for 15 years in ecological economics at the universities of Maryland and Vermont. He has authored or coauthored 150+ scientific publications, and has been recipient of major research grants from the US National Science Foundation, the European Union, the UK Natural Environment Research Council (NERC), UNEP-WCMC and other institutions and NGOs.

In 2007, Dr. Pérez co-founded K.B. Data Mining S.L., a company focused on the application of Machine Learning, Data Mining and optimization techniques to problems of biotechnology and industry, and he was the research manager until 2010. In 2010, Dr. Pérez finished his European thesis in the Intelligent System Group (UPV/EHU) about supervised classification with Bayesian networks in domains with mixed variables. He was a researcher at the Department of Computer Sciences and Artificial Intelligence from 2010 to 2014. Since 2011, Dr. Pérez has been an invited lecturer in the Master of Computational Engineering and Intelligent Systems of UPV/EHU. He has been a postdoctoral fellow at the Basque Center of Applied Mathematics (BCAM), from 2014. Since 2017, Dr. Pérez is a member of Join Research Lab with the participation of UPV/EHU, BCAM and Tecnalia Research & Innovation.

Since completing his Master’s in Environmental Economics, Dr. Balbi has studied human-natural systems interactions from a holistic perspective, where theories and approaches from both social and environmental scientific practice are integrated to better represent behaviors, spatial dependencies and temporal dynamics. This led him to pursue a PhD in Analysis and Governance of Sustainable Development and to direct his interests towards research in human geography, to explore the complexity of social-ecological systems.

Dr. Bustos is a Medical Oncologist and a Computer Science Engineer, with a PhD in Artificial Intelligence. With decades of experience as a medical doctor, she decided to study computer science and bring the two disciples together to further investigate how technology could help patients. She co-founded Medbravo, a platform to help research in cancer using technology, specifically deep learning, and she’s was awarded in 2019 the Civil Merit Award by the King of Spain Felipe VI as recognition of her efforts.

Dr. Díez-Oliván is a senior data scientist with more than 10 years of experience with machine learning applications. He received a Computer Science degree at UPV/EHU in 2006 and a M.Sc. in Computer Sciences and Artificial Intelligence in 2009 from the same University. He received his PhD degree in Robotics and Automation from the Technical University of Madrid in 2017, being his thesis related to machine learning methods and applications for data-driven prognostics. He entered Fatronik with the Iñaki Goenaga Research Fellowship in 2006 and in 2015 he did an internship at the NICTA’s machine learning research group in Sydney (Australia). Nowadays he works as a senior data scientist in the TECNALIA’s Industry & Transport Division. He has been involved in the design and development of intelligent applications in several R&D projects, addressing challenging data-driven problems.

Dr. Fernandes is a data scientist from computing and artificial intelligence studies with the skills and experience needed to translate the data into valuable information for marine research. These skills are curiosity, biological and oceanographic expertise, economic knowledge, ability to find information, understanding of statistics and machine learning and multidisciplinary communicative skills. Latest work and future line of research is about mitigation of impacts and long-term sustainability of fisheries using the above skills. This line of research contributes to address the Spanish Science and Technology Strategy challenges number 2 (bioeconomy), 5 (climate change) and 7 (digital society). It also aligns with SDG 14 challenge (ocean sustainability).

David is currently heading the Digital Transformations for Environmental Sustainability programme at UNEP. In this capacity, he is also leading UNEP’s co-championship of the new Coalition for Digital Environmental Sustainability (CODES) that is part of the UN Secretary General’s Digital Cooperation Roadmap. He holds an M.Sc. in Biology from Oxford University (UK) and an undergraduate degree in Geography from the University of Victoria (Canada). He is an Alumnus of the Peace Mediation Platform (Swiss Federal Department of Foreign Affairs) and a Beahrs’ Environmental Leadership Fellow at the University of California, Berkeley.

Dr. Langhans is a Marie Slodowska Curie Fellow at the University of Otago in Dunedin, New Zealand and BC3. She holds a Diploma in Natural Sciences, a MSc in Advanced Studies in Secondary and Higher Education, and a Doctor of Sciences from the Swiss Federal Institute of Technology in Zurich (ETH). Throughout her academic career, she has constantly broadened her expertise by joining research groups around the world. Besides academia, Dr. Langhans has experience working within government settings, having led the Swiss-wide development of river quality assessments for a few years after her PhD.

Dr. Marinescu has a PhD in Computer Science from UCSB. After a 1.5 years Postdoc at MIT she moved to IBM Research, and then back to Europe as a Visiting Professor in Madrid. She is currently working as a senior researcher at BSC in Barcelona.

Dr. Murillo has a degree in Business and Economic Sciences, University of the Basque Country/Euskal Herriko Unibertsitatea in San Sebastian. Master in System Development in Internet Environments. Master in Social Entrepreneurship, Leadership and Open Innovation. She is the president at the European level of the Smart City Tech alliance and Vice-president at the national level of the National Federation of Innovative Business Groups and Clusters. She represents GAIA in European and international alliances. She defines, designs and develops projects that directly or indirectly satisfy the needs of associated companies and other clients, as well as GAIA's internal needs. (regional, national and international). She coordinates the secretary of the artificial intelligence working group called AIBasque.

Dr. Oliver is a computer scientist. She is Chief Scientific Adviser at the Vodafone Institute, Chief Data Scientist at DataPop Alliance, an independent director on the board of directors of Bankia, and Commissioner of the Presidency of Valencia for AI and COVID-19. Previously, she was Director of Data Science Research at Vodafone, Scientific Director at Telefónica and researcher at Microsoft Research. She holds a PhD from the Media Lab at MIT, and is an IEEE Fellow, ACM Fellow, a member of the board of ELLIS, and elected permanent member of the Royal Academy of Engineering of Spain.

Dr. Orduna has a degree in Computer Science Engineering and a Diploma of Advanced Studies in the Complex Systems from UPV / EHU. He also has a PhD in the area of Computer Science and Artificial Intelligence by UPNA. Besides being Cybersecurity Director at Vicomtech, he is associate professor at UPNA.

Prof. Sanz holds a Ph.D. in Biological Sciences from the Universidad de Valencia (1991) and has expertise in several scientific areas like Ecophysiology, Air pollution effects, lower and higher plants, Atmospheric dynamics and chemistry, Nitrogen and carbon cycles, Greenhouse Gasses and other related gases, Greenhouse gas inventories, LULUCF and REDD+. She has been strongly involved in the policy dimension of Climate Change, guiding political decisions carried out at centres such as the FAO (United Nations Food and Agriculture Organisation) or the UNFCCC (United Nations Framework Convention on Climate Change). She has an expertise on multilateral processes, regulatory frameworks, policy measures and instruments of Climate Change Policy, and led the implementation of different programmes with a multidisciplinary-based approach.