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Research Scholar Exploratory Modeling of Human-natural Systems Research Group
Advancing Systems Analysis Program
+43(0) 2236 807 610
Dr. Valeria Javalera holds a PhD (cum laude) in Automatic and Robotics from the Polytechnic University of Catalonia (UPC) Spain, as well as an MSc in Computer Science, and an Engineering degree in Computer Systems from the Technological Institute of Hermosillo, Mexico. Her research focuses on developing Machine Learning (ML) algorithms for multi-objective and multi-agent optimization problems where a Pareto optimum is needed.
During the completion of her PhD, Dr. Javalera was a research assistant at the Institute of Robotics and Industrial Informatics (IRI). At IRI, she developed algorithms based on ML to optimize distributed Large-Scale Systems (LSS). Dr. Javalera applied this research to projects related to the integrated water cycle management, such as the WIDE project, funded by the European Union, and the WATMAN and ITACA projects financed by the Spanish government.
Dr. Javalera was an associate professor at the Higher Technological Institute of Cajeme (ITESCA) and has more than fifteen years of teaching experience at graduate and undergraduate level in the areas of distributed computing, multi-agent systems, artificial intelligence, and computer science. Dr. Javalera was also a member of the postgraduate council of Mechatronics at the institute. She is also a founding member of the Ibero-American Network in Artificial Intelligence (RIIA).
As a researcher at the Ecosystems Services and Management program, Dr. Javalera manages and develops the Linker platform. The Linker platform is a tool that links land-use models from more than 24 regions/countries participating in the FABLE project. Part of Dr. Javalera's work in FABLE, where is also a member of the secretariat, is to help to coordinate the collaboration between the different country teams towards to address some of the SDGs by aligning countries' land-use planning through sustainable international trade.
FABLE, (2020). Pathways to Sustainable Land-Use and Food Systems. 2020 Report of the FABLE Consortium. International Institute for Applied Systems Analysis (IIASA) and Sustainable Development Solutions Network (SDSN)
Rovenskaya, E. , Aghababaei Samani, K., Baklanov, A. , Ermolieva, T., Folberth, C. , Fritz, S., Hadi, H., Javalera Rincón, V. , et al. (2019). Artificial Intelligence and Machine Learning for Systems Analysis of the 21st Century. IIASA Working Paper. Laxenburg, Austria: WP-19-010
FABLE 2019, (2019). Pathways to Sustainable Land-Use and Food Systems. International Institute for Applied Systems Analysis (IIASA) and the Sustainable Development Solutions Network (SDSN)
Javalera Rincón, V. , Cayuela, V.P., Seix, B.M., & Orduña-Cabrera, F. (2019). Cooperative Linker for the Distributed Control of the Barcelona Drinking Water Network. In: Proceedings of the 11th International Conference on Agents and Artificial Intelligence (ICAART 2019). pp. 560-567 Porto, Portugal: ICAART. ISBN 978-989-758-350-610.5220/0007349105600567.
Javalera Rincón, V. , Cayuela, V.P., Seix, B.M., & Orduña-Cabrera, F. (2019). Reinforcement Learning Approach for Cooperative Control of Multi-Agent Systems. In: Proceedings of the 11th International Conference on Agents and Artificial Intelligence (ICAART 2019). pp. 80-91 Porto, Portugal: ICAART. ISBN 978-989-758-350-610.5220/0007349000800091.
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