Dr. Tom Cowton is a Senior Lecturer and Director of Teaching at the School of Geography and Sustainable Development, University of St Andrews. His research focuses on mechanisms controlling the response of glaciers, particularly the Greenland Ice Sheet, to climate change. He employs field studies, modeling, and remote sensing to investigate ice sheet hydrology, tidewater glacier processes, and fjord oceanography. Research Interests Subglacial hydrology and its impact on ice flow variability Fjord system dynamics and submarine melting processes Climate-glacier interactions in Greenland Glacier calving mechanics and plume-driven melting Publications highlight advancements in understanding fjord circulation, submarine melt rates, and calving dynamics. Recent work emphasizes the role of subglacial discharge plumes in subsurface warming and the influence of iceberg meltwater on oceanic heat flux. His studies contribute to modeling frameworks for predicting ice sheet responses to environmental changes. Dr. Cowton supervises PhD students Emma Cameron and William Spicer. He has no listed scientific awards. His research integrates interdisciplinary approaches to address critical questions in glaciology, climate science, and environmental sustainability.
Leonardo Azevedo is an Assistant Professor (with Habilitation since 2021) at the Department of Civil Engineering, Architecture and Georesources, Instituto Superior Técnico, University of Lisbon. His academic journey includes a PhD in Georesources from IST (2013), with visiting periods at Stanford University and Heriot-Watt University, and earlier degrees from Aveiro University. He specializes in geostatistical methods for reservoir characterization and seismic inversion, with applications to carbon sequestration, subsurface modeling, and environmental geophysics. Research interests focus on integrating geostatistics with advanced computational techniques, including machine learning and generative adversarial networks (GANs), to improve subsurface modeling accuracy. Key areas include seismic inversion for reservoir properties, uncertainty quantification, and geophysical data interpretation. He has supervised numerous PhD and MSc students, with topics ranging from geostatistical CO2 plume modeling to seismic oceanography. Awards include the Fulbright Scholarship (2018-2019) and recognition for top-tier SEG conference contributions (2015). His work has been published in journals like Geophysics , Computational Geosciences , and Mathematical Geosciences . He leads the EVOLVE team (2018) and advises student chapters of SEG and SPE. Current funded projects include the SMART project for marine debris monitoring and stochastic rock physics inversion research. His industry experience includes roles at Parallel Geoscience and CGG, bridging academic and applied geophysics.
Dr. Ioana Colfescu is a Principal Research Fellow in Climate and Machine Learning at the University of St Andrews' School of Earth & Environmental Sciences, with a joint role at the National Centre for Atmospheric Science (NCAS). She leads the NCAS St Andrews research group, specializing in physics-informed machine learning for climate system analysis. Her academic roles include Digital Atmosphere Programme Leader at NCAS and teaching specialized atmospheric science courses. Colfescu holds a PhD in Climate Dynamics from George Mason University and degrees from the University of Bucharest. Her research focuses on large-scale climate dynamics (ENSO/AMO), machine learning applications for climate prediction, extreme events, and mountain meteorology, with notable contributions to North Sea emissions studies and mountain wave modeling. She has collaborated with institutions worldwide, including the National Centre for Atmospheric Research (USA) and universities in Italy, Spain, and Romania. Colfescu's fieldwork spans the Arctic, Iceland, and Italy, and she is a Certified Mission Scientist for airborne research. She actively mentors postgraduate students, emphasizing collaborative, cross-disciplinary approaches. Her work bridges fundamental climate science with applied impacts, supported by industry and international research partnerships.
Ana B. Ruescas is an Associate Professor in the Department of Geography and a Researcher at the Image and Signal Processing Group (ISP) and Laboratorio de Procesado de Imagenes (LPI) at the University of Valencia. She holds a PhD in Geography from the University of Jaume I (2006) and an MSc in GIS (2003). Her career includes roles at ESRIN (ESA) and Brockmann Consult as a Remote Sensing Specialist. Research focuses on remote sensing applications for environmental monitoring, particularly in water quality, climate change, and satellite data analysis. She has pioneered work on ocean carbon dynamics, machine learning for optical water type classification, and algorithm development for Sentinel missions. Her interdisciplinary work bridges Earth observation with education, including AI-driven educational tools and service-learning projects in protected areas. Key contributions include the SEN4LST project (LST retrieval from Sentinel data), GLaSS project (inland water quality monitoring), and ERC SEDAL project. She has over 70 publications, including peer-reviewed articles on oceanography, machine learning applications, and geospatial education. Her work has been cited over 800 times, highlighting her impact in environmental remote sensing and education technology. Current projects involve advancing satellite-derived water quality metrics, AI integration in environmental data analysis, and sustainable development through Earth observation. She actively collaborates with international teams and contributes to UNESCO/ESA initiatives on World Heritage site conservation.
Daniela Domeisen is an Associate Professor of Atmospheric Processes at the Institute for Land Surface Dynamics (IDYST), University of Lausanne (UNIL). Her academic career includes roles as an Assistant Professor at GEOMAR Helmholtz Centre for Ocean Research Kiel and Christian-Albrechts-Universität zu Kiel, where she led the 'Atmospheric Dynamics and Predictability' group. She holds a PhD in Climate Physics and Chemistry from MIT, complemented by postdoctoral research at Cornell University and the University of Hamburg. Education: Bachelor's in Physics at ETH Zurich Master's in Climate and Society at Columbia University PhD in Climate Physics and Chemistry from MIT (2012) Mini-MBA from Harvard Business School (2012) Research Interests: Atmospheric fluid dynamics theory and predictability Vertical processes within the atmosphere Tropical-extratropical interactions Subseasonal forecasting (weeks-months) Rossby waves and their role in extreme weather Articles Trends: Recent work focuses on Rossby wave dynamics, stratospheric influences on weather extremes, and machine learning applications in forecasting. Key themes include heatwave predictability, teleconnections from climate oscillations (e.g., MJO, ENSO), and climate model improvements. Awards & Grants: ERC Starting Grant SNSF Professorship Grants & Advising: Leads projects on subseasonal heatwave prediction and European windstorm damage projections. Her work bridges theoretical atmospheric science with practical forecasting applications. Labs/Teams: Active in the UNIL IDYST research group and collaborates with institutions like ETH Zurich, MIT, and international meteorological organizations.
Jorge Pérez Aracil is an academic researcher at the Department of Signal Theory and Communications at the University of Alcalá. His work focuses on applying artificial intelligence and optimization algorithms to solve complex problems in climate science, renewable energy systems, structural engineering, and extreme event prediction. He leads the GHEODE research group, specializing in modern heuristic optimization techniques for network design and environmental modeling. His research interests span multiple disciplines including machine learning for weather prediction, metaheuristic algorithms for engineering design, vibration isolation systems, and the integration of AI with numerical models for climate analysis. Notable contributions include hybrid deep learning frameworks for energy forecasting, spatio-temporal analysis of droughts, and AI-driven models for understanding heatwaves and their socio-economic impacts. Recent work emphasizes extreme event modeling through projects like Spain on fire (wildfire risk assessment via satellite data) and Autoencoder-based flow-analogue methods for reconstructing heatwaves. He also explores pedagogical innovations, such as hybrid flipped/project-based learning models for AI-era education. Key technical contributions include the CRO-SL optimization algorithm, used in applications ranging from smart grid management to structural design optimization. His publications often bridge theory and practice, with a focus on explainability in AI systems and real-world implementation challenges.
Raúl Vicen Bueno is a Researcher at the University of Alcalá's Department of Electrical Engineering, affiliated with the AES3 research group focused on Acoustic and Electromagnetic Smart Sensor networks and Signal processing. He holds a PhD from the University of Alcalá, awarded in 2012 for his thesis on 'Automatic detection of signals by using artificial intelligence techniques,' supervised by Dr. Manuel Rosa Zurera and Dr. María del Pilar Jarabo Amores. His research interests include signal processing, sensor networks, maritime communication, and AI applications in environmental and military contexts. His work emphasizes optimizing underwater communication systems, securing underwater cables, and developing autonomous glider technology for naval operations. He has actively participated in NATO exercises such as CWIX 2016/2017, showcasing interoperable glider command-and-control capabilities. Notable contributions include the GliderC2 system, environmental condition-based algorithms, and sensor integration frameworks for anti-submarine warfare and maritime surveillance. Raúl has published extensively on sensor networks, underwater robotics, and decision support systems, with a focus on real-time data provision and environmental modeling. His articles address challenges in optimizing node movement in underwater networks, securing communication cables, and enhancing tactical decision-making through algorithmic innovation. He has also contributed to workshops and conferences on military applications of underwater glider technology, emphasizing future research directions and technological advancements. His academic contributions span both theoretical and applied domains, bridging electrical engineering, computer science, and maritime security. Collaborative efforts with institutions like CMRE (NATO Undersea Research Centre) highlight his role in developing practical solutions for naval operational effectiveness and environmental monitoring.
Rupert Gladstone is a Researcher at the Arctic Centre, University of Lapland, specializing in ice sheet modeling and sub-glacial processes. His work focuses on Antarctic and Greenland ice dynamics, particularly ice-ocean interactions and grounding line stability. He has been actively involved in projects such as CLIM2Ant (2024-2027) and ICEMAP (2023-2027), addressing sea level rise projections and machine learning applications in glaciology. Key research areas include computational efficiency in ice-ocean coupling, basal melt parameterization, and subglacial hydrology. Gladstone has contributed to over 48 publications since 2001, with recent work emphasizing model intercomparison (e.g., MISOMIP1) and projections of ice sheet behavior under climate change. His projects often involve international collaborations, such as with Norway’s Research Council and the Research Council of Finland. Publications highlight advancements in understanding Thwaites Glacier dynamics, Wilkes Subglacial Basin stability, and the impact of mélange buttressing. He has also explored geoengineering concepts for mitigating sea-level rise. Current research trends prioritize integrating machine learning with ice sheet models and quantifying uncertainties in Antarctic ice evolution.
Prof. Attilio Sulli is a Full Professor in Earth and Marine Sciences at the University of Palermo. His research focuses on marine geology, tectonics, and geohazard analysis, with specific interests in the central Mediterranean and Latin America. He leads projects like SIRIPRO (seismic data analysis in Sicily) and MAGIC (marine geohazards assessment), collaborating with institutions such as INGV, CNR, and international universities. His work integrates sedimentology, seismostratigraphy, and coastal management, addressing topics like fluid escape processes, fault activity, and underwater landslide risks. He operates advanced laboratories for grain analysis and seismic interpretation, and provides third-party services in geological mapping and resource exploration. Key collaborations include the National Oceanography Centre (UK), University of Malta, and Brazilian institutions like USP São Paulo. His research spans structural surveys of Sicily's stratigraphy, continental margin dynamics, and geochemical studies of mantle volatiles. Recent projects address tsunami hazard modeling, CO2 storage potential in marine basins, and paleoenvironmental reconstruction using isoradiometric methods. Notable achievements include 3D Moho modeling in the Sicily Channel, thermal-structural modeling of fold-and-thrust belts, and the identification of pockmark-fluid linkages. His work bridges academic research with applied geology, informing coastal management and energy resource assessments.
Padmanava Dash is an Associate Professor in the Department of Geosciences at Mississippi State University (MSU), specializing in remote sensing and water biogeochemistry. His work integrates satellite, unmanned aerial systems (UAS), and autonomous surface vessels to monitor and model water quality parameters such as harmful algal blooms, suspended sediments, nutrients, and heavy metals. He leads the development of web-based visualization tools for water quality management and supports federal, state, and coastal community initiatives. Education Ph.D. in Oceanography and Coastal Sciences, Louisiana State University, 2011 M.S. in Geology, Bowling Green State University, 2005 Research Interests Dr. Dash’s research is centered on understanding the drivers and consequences of water quality degradation in aquatic systems. Using multi-scale remote sensing techniques—from handheld spectrometers to satellites—he quantifies spatiotemporal patterns of phytoplankton blooms, dissolved organic matter, acidification, and trace metals. Advanced machine-learning algorithms are routinely integrated to improve retrieval accuracy and predictive capacity, enabling early warning systems for human and ecological health risks. A significant component of his portfolio involves the design and deployment of autonomous platforms (UAS and ASV) for high-resolution, real-time data acquisition. These efforts feed into web portals that translate complex geospatial data into intuitive maps and dashboards for stakeholders, thereby bridging the gap between science and policy. Publication Trends Between 2024 and 2025, Dr. Dash has published extensively on three converging themes: (1) machine-learning-enhanced retrieval of water quality parameters from satellite and UAS imagery, (2) geochemical immobilization of iodine and uranium using phosphate minerals for nuclear waste management, and (3) physical-biological interactions in marine systems such as mesoscale eddies and hypoxia in the Gulf of Mexico and Bay of Bengal. The work spans freshwater lagoons, estuaries, and coastal oceans, demonstrating a commitment to transdisciplinary, data-driven environmental science. Scientific Awards No specific awards are listed in the provided materials. Advising & Funding While current Ph.D. or master’s students are not named in the text, Dr. Dash’s active laboratory and consistent publication record suggest ongoing mentoring and grant support. External collaborations span federal agencies (NASA, NOAA), state departments of environmental quality, and international partners in India’s Chilika Lagoon. Laboratory & Field Infrastructure Dr. Dash operates the Remote Sensing and Water Quality Lab at MSU, equipped with hyperspectral sensors, UAS platforms, autonomous surface vessels, and high-performance computing resources. The lab maintains two public web tools for real-time water quality visualization accessible at water.geosci.msstate.edu .
William T Sloan is a Professor of Environmental Engineering at the University of Glasgow's Infrastructure & Environment College, Department of Civil Engineering. He holds the Royal Academy of Engineering Chair in Emerging Technologies (since 2020). His research focuses on engineered biological systems, microbial community modeling, biofilms, and off-grid water technologies. Education : PhD in Civil Engineering (University of Newcastle Upon Tyne, 2000), MSc in Physical Oceanography (University College of North Wales, 1987), BSc in Mathematics (Heriot-Watt University, 1986). Research : Sloan’s work bridges environmental engineering and microbiology, emphasizing mathematical modeling of microbial systems. Key areas include drinking water biofiltration, biofilm dynamics, and anaerobic digestion optimization. He employs machine learning and advanced sensors for water quality assessment. Grants/Awards : EPSRC Advanced Research Fellow (2007–2013), NERC Discipline Hopping Fellow (2002–2003). Active in interdisciplinary projects, including sustainable waste-to-energy systems and climate resilience in water infrastructure. Labs/Teams : Leads research groups in microbial ecology and environmental biotechnology, collaborating with international partners on projects like solar septic tanks and groundwater modeling in UAE/Thailand.
Professor Stephen Turnock is Head of Civil, Maritime and Environmental Engineering at the University of Southampton, leading a 50-strong academic department. Previously head of the Maritime Engineering Group, he founded the Maritime Robotics Laboratory in 2008 and established the Performance Sports Engineering Laboratory (awarded Queen's Anniversary prize in 2012). As Academic Lead at the Boldrewood Towing Tank since 2012, he currently oversees development of a £25M Fluids Research Complex featuring a 138m tow/wave tank with 12m/s carriage speed and 0.9m wave height capabilities. PhD, University of Southampton, Ship Science, 1993 MA, University of Cambridge, Pembroke College, 1990 SM, Massachusetts Institute of Technology, 1988 Professor Turnock's research spans maritime decarbonization, robotics, autonomous systems, and performance sports engineering. His expertise lies in synthesizing analytical, experimental, and computational methods for diverse applications including ship hydrodynamics, underwater vehicle development, and sports performance optimization. His work encompasses hull-propeller-rudder interaction, maneuvering in waves, underwater noise prediction, and renewable energy from environmental flows. He has applied his knowledge to Olympic sports equipment design, tidal energy generation, and autonomous underwater vehicles. His recent publications demonstrate a strong focus on sustainable maritime technologies, with significant emphasis on decarbonization strategies, autonomous navigation systems, and fluid dynamics optimization. The research spans theoretical developments, experimental validations, and practical implementations addressing critical challenges in maritime transport and environmental protection. Lead Academic for Queen's Anniversary Award (2012) JEME Annual Best Paper Prize (2010) Outstanding Achievement Award (2027) The Engineers' Energy Sector Innovation award (2008) The Engineer's Sport Technology Innovation award (2010) SAUC-E competition winner (2007) Professor Turnock leads a substantial research team with funding from diverse sources including EPSRC, dstl, EU, UK Sport, and industry partners. He has supervised over 50 PhD students whose careers span the maritime sector, performance sports, renewable energy, and academia worldwide. His current supervision includes eleven PhD students working on projects ranging from autonomous underwater vehicles to carbon capture transport. He founded the Performance Sports Engineering Laboratory (awarded Queen's Anniversary Prize in 2012) and the Maritime Robotics Laboratory in 2008. His current leadership of the £25M Fluids Research Complex development represents a major infrastructure advancement for maritime research at Southampton, supporting the UK's maritime decarbonization goals and autonomous shipping initiatives.
Alexandre Gagnon is a Reader in Climatology at Liverpool John Moores University's School of Biological and Environmental Sciences (2024–present), where he focuses on climate change adaptation, vulnerability assessments, and sustainable water resource management. Previously, he held roles as Senior Lecturer in Geography (Climate Change) at the same institution (2018–2024), Lecturer at the University of the West of Scotland (2007–2018), and Research Fellow at the University of Highlands and Islands (2006–2007). He earned a PhD in Geography from the University of Toronto (2000–2004) and a master's degree from the University of Alberta (1998–2000). Education: PhD in Geography, University of Toronto (2004) MSc in Geography, University of Alberta (2000) His research spans climate change impacts on coastal and agricultural systems, GIS and remote sensing applications, machine learning for environmental modeling, and water security in vulnerable regions like Vietnam, India, and Madagascar. Recent publications emphasize drought stress prediction, salinity variability, solar desalination suitability, and traditional housing resilience to extreme weather. Key article trends include integrating multi-criteria decision analysis for renewable energy planning, process modeling for water security, and bio-stabilization techniques for heritage construction. His work often combines climate projections , field studies , and stakeholder engagement across interdisciplinary domains. He has collaborated extensively with researchers in South Asia , Madagascar , and Pakistan , addressing coastal vulnerability , glacier dynamics , and agricultural sustainability . While no formal advising roles are listed, his publications frequently involve junior researchers and multidisciplinary teams.
Lai-yung (Ruby) Leung is a Battelle Fellow at Pacific Northwest National Laboratory with a courtesy appointment at Oregon State University's College of Earth, Ocean, and Atmospheric Sciences. She serves as Chief Scientist of the Energy Exascale Earth System Model (E3SM) supported by the U.S. Department of Energy and has organized key workshops sponsored by major scientific agencies including DOE, NSF, NOAA, and NASA. Dr. Leung's research spans climate and hydrological cycle modeling, land-atmosphere interactions, orographic processes, monsoon climate, climate extremes, land surface processes, and aerosol-cloud interactions. Her work on climate change impacts has been featured in Science, Popular Science, Wall Street Journal, National Public Radio, and major newspapers worldwide. She has published over 500 peer-reviewed papers and serves as editor for the American Meteorological Society's Journal of Hydrometeorology. Her recent publications demonstrate expertise in high-resolution climate modeling, mesoscale convective systems, land-atmosphere feedbacks, and climate extremes. Her work increasingly incorporates machine learning approaches for climate prediction and model evaluation, while maintaining focus on fundamental physical processes in Earth system models. Elected Member, National Academy of Engineering Elected Member, Washington State Academy of Sciences Fellow, American Geophysical Union Fellow, American Meteorological Society Fellow, American Association for the Advancement of Science AMS Hydrologic Sciences Medal, 2022 U.S. Department of Energy Office of Science Distinguished Scientist Fellow, 2021 Reuter's Hot List of top 1,000 climate scientists, 2021 Dr. Leung serves on advisory panels and National Academies committees defining future priorities in Digital Twin, AI/ML, climate modeling, hydroclimate, and water cycle research. She has been invited to deliver numerous distinguished lectures globally, including the Snoeyink Distinguished Lecturer at University of Illinois and Inaugural Leaders in Discovery Lecture Series at University of Iowa.
Rafael Garcia Campos is a tenured Professor at the University of Girona 's Department of Architecture and Computer Technology, with a career spanning 20+ years. He serves as Director of the Computer Vision and Robotics Institute (VICOROB) and leads the Underwater Vision Lab. His work bridges computer vision , robotics , and marine exploration , with leadership roles in European projects like iToBoS and DeeperSense. Active in 3D optical mapping , autonomous underwater vehicles , and deep learning applications, he has received grants from H2020, MINECO, and FP7. PhD in Computer Engineering (University of Girona, 2001) MSc in Computer Engineering (University Autònoma de Barcelona, 1994) Research focuses on underwater imaging , autonomous navigation , and computer vision algorithms for seafloor exploration , coral reef monitoring , and medical imaging . His publications emphasize real-time perception , sensor fusion , and 3D reconstruction in challenging environments like polarized underwater scenes and defective point clouds. Grant highlights include: iToBoS Project (2021-2024): €1.14M (Coordinator) DeeperSense (2021-2023): €475K SIREC (2021-2024): €249K He has delivered keynote lectures globally on topics like underwater perception and autonomous marine systems , and co-authored books on 3D scene modeling and underwater mosaicing. His lab techniques have been commercialized through contracts with institutions like the University of Miami and Nova Southeastern University.
