Dr. Marina Vicens-Miquel is a Postdoctoral Fellow in Meteorology and Computer Science at the University of Oklahoma, a role she began in August 2024. Her research focuses on enhancing the accuracy, uncertainty quantification, and explainability of extreme precipitation predictions through advanced machine learning techniques. Dr. Vicens-Miquel has a strong background in research, having worked as a Research Assistant at the Lone Star UAS Center of Excellence and Innovation (LSUASC) from January to May 2020, followed by her position as a Graduate Research Assistant at the Conrad Blucher Institute (CBI) from September 2020 to May 2024, and later as a Research Program Associate II at CBI from May to July 2024. She has been part of the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES) since September 2020. Dr. Vicens-Miquel earned her Ph.D. in Geospatial Computer Science from Texas A&M University-Corpus Christi in May 2024. Prior to her Ph.D., she completed a double major in Computer Science and Mathematics at Texas A&M University-Corpus Christi in 2020.

Philippe E. Tissot is the Conrad Blucher Institute Chair for Coastal Artificial Intelligence at Texas A&M University-Corpus Christi and a Co-PI for the National Science Foundation Artificial Intelligence Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). His research is focuses on the development, with his students, of artificial intelligence methods for the analysis and predictions of environmental systems with a focus on coastal physical processes. The research includes the adaptation of rapidly evolving AI methods such as ensemble models, uncertainty quantification, or XAI to potentially gain insights into the dynamic of coastal processes. Models are deployed operationally to help predict coastal inundation, navigation, and emergency management including to help mitigate the impact of sea turtle and fisheries cold stunning events. Other research includes studying relative sea level rise, the spatial variability of vertical land motion, and their societal impacts. Dr. Tissot received a Diploma (MS) in physics engineering from the Swiss Federal Institute of Technology, Lausanne, Switzerland, in 1987 and a Ph.D. in nuclear engineering from Texas A&M University, College Station, TX, USA, in 1994. Prior to joining TAMU-CC, Dr. Tissot worked as a research scientist at a private research institution with R&D projects including semiconductor materials analysis, treatment of engineered wood materials, and prototypes for oil exploration.

F. Antonio Medrano is an Assistant Professor of Geospatial Computer Science at Texas A&M University-Corpus Christi and the director of the Geospatial Optimization & Analytics Lab (GOAL), focusing on geospatial computation research. He earned his Ph.D. in Computational Geography at the University of California, Santa Barbara (2014), his MS in Multimedia Engineering at UC Santa Barbara (2009), and his BS in Engineering at Harvey Mudd College (2002). He served as Visiting Professor at the Universitat Jaume I, Castellón de la Plana, Spain (September–October 2015), as Postdoctoral Researcher at the Center for Spatial Studies, Department of Geography, UC, Santa Barbara (April 2015–January 2016), and as Postdoctoral Researcher at the Bren School of Environmental Science & Management, UC, Santa Barbara (August 2017–December 2018). He co-founded Arogi, Inc., Santa Barbara, CA (February 2016–February 2017). In January 2019, he joined Texas A&M University–Corpus Christi. His research centers on location decisions, such as point and path location problems to optimize facility utility given resource constraints. The topics of his research include fast optimization algorithms and heuristics, multi-objective optimization, diverse near-optimal solutions, and parallelization of network algorithms for use on high-performance computing resources.