Xingong Li is a Professor and Director of Undergraduate Studies in the Department of Geography at the University of Kansas. His research focuses on geospatial technologies for analyzing surface water dynamics, terrain analysis, and spatiotemporal data frameworks. He teaches courses in spatial analysis, geospatial programming, and water resources applications. His work integrates remote sensing, GIS, and computational models to address environmental challenges such as lake dynamics, solar radiation modeling, and climate impacts on hydrology. Key research interests include: surface water mapping, terrain shading algorithms, and spatiotemporal data frameworks. He has published extensively in journals like Remote Sensing of Environment, Transactions in GIS, and Water Resources Research. Recent studies investigate Tibetan Plateau lake changes, solar radiation modeling in mountainous regions, and GIS applications for cultural heritage mapping. Publications span 1995–2022 with over 50 peer-reviewed articles. His work bridges computational methods with environmental science, emphasizing interdisciplinary GIS applications.
Aziz Zanjani is a Postdoctoral Researcher at the Roy M. Huffington Department of Earth Sciences, Southern Methodist University. His research focuses on induced seismicity, seismotectonics, and crustal structure analysis using advanced geophysical techniques. Key areas include spatiotemporal evolution of earthquakes in the Delaware Basin, machine learning applications for seismic event detection, and tomographic imaging of continental rifts. Research interests emphasize induced seismicity linked to oil/gas activities, subduction zone dynamics, and crustal deformation processes. Methodologies include P-wave tomography, surface-wave analysis, and relocation algorithms to improve earthquake catalog accuracy. He has conducted studies in regions like the Wabash Valley Seismic Zone, Puerto Rico subduction zone, and Iran's North Tehran Fault. Recent work highlights use of machine learning for seismic event detection in Texas/Oklahoma oil fields and integration of dense seismic array data to resolve complex fault geometries. His portfolio reflects interdisciplinary approaches bridging geophysics, tectonics, and computational methods. No scientific awards or formal advising roles are explicitly noted in current records. Ongoing projects likely involve real-time seismic monitoring and improved hazard assessment frameworks.
Abdourrahmane ATTO is a Professor at Polytech Annecy-Chambéry, part of Savoie Mont-Blanc University. His research focuses on advanced machine learning techniques, including deep learning theory, stochastic modeling of multi-fractal processes, and time series analysis of images. He specializes in applications such as SAR image processing, environmental monitoring, and geohazard prediction. His work integrates neural networks, wavelet analysis, and explainable AI methods. Research Themes: Deep Learning Theories (Analysis, Explainability) Multi-Fractality and Stochastic Modeling Time Series of Images & Video Analysis Convolutional Neural Networks SAR and InSAR Image Processing Key Contributions: Developed timed-image representations for action recognition in video sequences. Advanced fractional Brownian field models for texture synthesis and analysis. Created the ISSLIDE dataset for landslide detection using machine learning. Pioneered explainable AI methods for hydrological forecasting and SAR image classification. Labs & Affiliations: Active member of LISTIC laboratory, focusing on interdisciplinary research in signal processing and computer science.
Professor Lewis Mitchell is a faculty member in the School of Computer and Mathematical Sciences at the University of Adelaide. He holds the academic rank of Professor and specializes in Data Science. His research focuses on computational social science, human dynamics, online social networks, and the mathematics of weather and climate. He applies mathematical models and data science techniques to study information flow in social networks and cardiac dynamics. Professor Mitchell's work spans diverse areas such as predicting wildlife trade risks, analyzing misinformation during crises, and modeling cardiac fibrillation using statistical frameworks. His recent publications (2023–2025) emphasize network analysis, causal discovery, and applications of machine learning in healthcare and environmental science. No awards or grants are explicitly listed in the provided texts. He has no listed advisees/students, and no lab affiliations are mentioned. His research leverages interdisciplinary methods, combining mathematical theory with real-world data-driven approaches.
Yuqin Jiang is an Assistant Professor in the Department of Geography at the University of Hawai'i at Mānoa, leveraging spatial big data to advance understanding of human mobility and human-environment interactions for sustainable urban development. Her research bridges data science and social sciences through quantitative methods addressing real-world societal challenges. Her academic credentials include: Postdoctoral Fellowship in Geography and Environmental Studies, Texas State University (2023-2024) Postdoctoral Fellowship in Civil and Environmental Engineering, Texas A&M University (2022-2023) PhD in Geography, University of South Carolina (2022) MS in Geography, University of South Carolina (2017) BA in Geography, University at Buffalo, SUNY (2014) Dr. Jiang's research program focuses on extracting actionable insights from massive spatial datasets to address critical urban challenges. Key areas include: Modeling human mobility during disruptive events like hurricanes and pandemics Developing equity-centered frameworks for post-disaster recovery Mapping healthcare accessibility and transportation dynamics Quantifying environmental impacts through activity-based carbon footprint analysis Creating cyberGIS tools for democratizing geovisual analytics Her recent publications (2020-2025) demonstrate consistent innovation in spatial big data applications, with increasing emphasis on methodological rigor and societal impact. Notable trends include the integration of diverse data sources (taxi GPS, mobile devices, social media) to uncover urban system patterns, growing attention to spatial inequality in environmental outcomes, and pioneering work in AI-assisted disaster response. She has developed novel approaches like entropy-based trip distribution measurements and sensor-based event detection systems. Dr. Jiang teaches GEO 388: Introduction to GIS Research and actively pursues interdisciplinary collaborations to expand the real-world applicability of her work in urban sustainability and disaster resilience.
Dr. Matthew Knowling is a Senior Lecturer and Research Program Lead in Decision Agriculture at the University of Adelaide's School of Agriculture, Food and Wine, within the Faculty of Sciences, Engineering and Technology. His work focuses on developing decision support tools that integrate data from agronomy, hydrology, economics, and engineering to address agricultural sustainability challenges. He leads the $7.6M GRDC Farming Systems South program, evaluating profitability and sustainability in southern Australian farming systems, and previously directed the VitiVisor project, enhancing vineyard management through data assimilation and forecasting. He is eligible to supervise Master's and PhD students in agricultural systems analysis. Research Interests: Decision Agriculture, sustainable resource management, process-based modeling, data assimilation, climate risk assessment, and interdisciplinary approaches to agricultural decision-making. His work emphasizes translating complex data streams into actionable strategies for farmers, businesses, and policymakers. Grants & Programs: GRDC Farming Systems South ($7.6M): Evaluates strategic and tactical decisions in water-limited farming systems, focusing on profitability, sustainability, and emerging practices. VitiVisor ($5M): Developed decision support tools for Riverland vineyards, integrating sensors, financial benchmarks, and grapevine dynamics models. Labs & Teams: Part of the Decision Agriculture team at the Waite Campus, collaborating with multidisciplinary groups to advance precision agriculture and sustainable practices.
Dr. Pin Shuai is an Assistant Professor in the Department of Civil and Environmental Engineering at Utah State University, affiliated with the Utah Water Research Laboratory (UWRL) within the College of Engineering. He leads the Shuai Computational and Integrated Hydrology (SCI-Hy) research group, focusing on advancing the understanding of complex hydrological systems through computational modeling and data integration. Dr. Shuai holds a PhD in Geology (Hydrogeology) from Texas A&M University (2017), an MS in Water Resources Engineering from Wuhan University (2013), and a BS in the same field from Wuhan University (2011). His academic journey was followed by a postdoctoral and staff scientist position at the Pacific Northwest National Laboratory from 2017 to 2022. His research interests are centered on groundwater-surface water interactions, nutrient and contaminant transport, watershed biogeochemistry, and integrated hydrologic modeling. He employs a model-data integrative approach combining field observations, laboratory data, remote sensing, and numerical models powered by high-performance computing. His group emphasizes open-source and reproducible science, addressing critical environmental challenges such as human-water interactions and the impacts of disturbances like drought and land use change on watershed processes. The recent publications of Dr. Shuai reflect a strong trend toward computational hydrology, with a focus on high-resolution watershed modeling, the role of streambed representation, the impact of meteorological forcing resolution, and the application of machine learning and deep neural networks for model calibration and permeability estimation. His work bridges traditional hydrological modeling with modern data science techniques, aiming to improve predictive capabilities in complex hydrological systems. Dr. Shuai has mentored several graduate students, including Collins Stephenson, Ehsan Ebrahimi, Pamela Claure, and Jihad Othman, guiding them through thesis research in civil and environmental engineering. While no scientific awards are listed in the provided text, his active research program, consistent publication record in high-impact journals, and leadership of a growing research group indicate a strong trajectory in the field. He teaches courses such as Groundwater Engineering, Hydrologic Modeling, and GIS for Civil Engineers, contributing to both graduate and undergraduate education. The SCI-Hy group, under Dr. Shuai’s leadership, is actively engaged in projects that integrate advanced modeling tools like the Advanced Terrestrial Simulator (ATS) and Watershed Workflow to parameterize and simulate watershed processes. The group welcomes passionate students and recently advertised for a postdoctoral position focused on ML/AI applications in hydrology, highlighting its forward-looking research direction.
Thomas Pulka is a researcher at the Institute of Hydrology and Water Management within the Department of Landscape, Water and Infrastructure at the University of Natural Resources and Life Sciences, Vienna (BOKU). His work focuses on high-alpine hydrological processes, particularly precipitation correction modeling, snow dynamics, and climate change impacts on water cycles. Education: Master of Science in Environment and Bioresources Management (2018–2021), Technical Management with Environmental Engineering specialization (2012–2015), Bachelor in High Tech Manufacturing with Social Systems management (2011–2012) His research emphasizes improving runoff forecasts for hydropower generation through snow cover modeling and addressing water level fluctuations in Kenyan Rift Valley lakes. Current projects include spatiotemporal precipitation analysis and glacier melt contributions to runoff. Key collaborations include work with VERBUND Trading GmbH and the European Geosciences Union (EGU). His publications highlight applications of conceptual hydrological models and snow depth pattern analysis in high-alpine catchments. Location: Muthgasse 18, 1190 Wien Email: thomas.pulka@boku.ac.at ORCID: 0000-0003-1916-3603
Michael Stockinger is a researcher at the Institute of Soil Physics and Rural Water Management , Department of Landscape, Water and Infrastructure, University of Natural Resources and Life Sciences, Vienna (BOKU). His work focuses on hydrology, isotope analysis, and water resource management, with particular emphasis on groundwater-surface water interactions, vadose zone dynamics, and catchment-scale hydrological processes. He leads projects such as Beech Forest Resilience Against Drought (2025–2027) and Towards Repeatable Catchment Experiments (2021–2025), funded by the Austrian Science Fund (FWF) and Austrian Research Promotion Agency (FFG). Education: Diploma in Land and Water Management and Civil Engineering (BOKU, 2001–2009) PhD: Institute of Bio- and Geosciences (IBG-3), Jülich Research Center, Germany (2011–2015) His research explores water transit time distributions, young water fractions, and stable isotope applications to study vegetation water use, groundwater recharge, and runoff generation mechanisms. He contributes to methodological frameworks for Critical Zone isotope analysis and investigates hydrological similarity across catchments using repeating runoff patterns. Recent projects include isotopic hydrograph separation in Austria’s Hydrological Open Air Laboratory and the COST Action WATSON (Water Isotopes in the Critical Zone). He has published extensively on topics like throughfall sampling innovations, soil moisture-vapor equilibration methods, and spatiotemporal analysis of water age dynamics. Michael Stockinger supervises students in the Institute of Soil Physics and Rural Water Management, with thesis topics ranging from throughfall collection methods to energy-water nexus studies. His work bridges field hydrology, isotopic tracing, and sustainable water management, particularly in agricultural and forested ecosystems.
Christian L. Vestergaard is a CNRS researcher (Researcher rank) in the Decision and Bayesian Computation group within the Department of Neuroscience at the Institut Pasteur, Paris. He holds a PhD in theoretical biophysics from the Technical University of Denmark and has held postdoctoral positions at the Institut Pasteur, Center for Theoretical Physics (Marseille), and DTU Nanotech. He currently leads research projects on neural connectomes and numerical methods for network analysis. Education: PhD in Theoretical Biophysics, DTU Nanotech, Technical University of Denmark (2008–2012) Master’s in Physics and Biophysics, Niels Bohr Institute, University of Copenhagen (2003–2008) Exchange Semester, UPMC, Paris (2007) Second-Year Master’s in Complex Systems His research lies at the intersection of statistical physics, biophysics, and computational neuroscience. He focuses on data-driven modeling of complex dynamical systems, particularly in biological contexts such as neural networks, single-molecule dynamics, and behavioral analysis. His work emphasizes the development of statistical and computational methods to infer structure-function relationships in biological systems. The analysis of his recent publications reveals a strong trend toward methodological innovation in network science, Bayesian inference, and machine learning applied to neuroscience and biophysics. Key themes include temporal network modeling, stochastic processes, information maximization in decision-making, and high-throughput behavioral phenotyping in Drosophila. His work combines theoretical rigor with practical applications in biological data analysis. Scientific Awards and Grants: ANR JCJC grant — SiNCoBe (2021–2024) ANR Inception grant — BitesGoingViral (2022–2024) ANR PR[AI]RIE Springboard Chair (2021–2023) ACIP Inter-Institut Pasteur Concerted Actions grant — ETHOMOS (2019–2021) Pasteur-Roux-Cantarini postdoctoral fellowship (2017–2019) Copenhagen Graduate School pre-doc stipend (2008) Christian L. Vestergaard actively collaborates with principal investigators such as Jean-Baptiste Masson and François Laurent. He has been involved in advising PhD students and postdoctoral researchers within the lab, contributing to interdisciplinary projects that integrate physics, computer science, and biology. His group utilizes advanced computational tools and software such as TRamWAy and LarvaTagger for analyzing large-scale biological datasets. Laboratories and Research Teams: Decision and Bayesian Computation Lab, Institut Pasteur (current) Statistical Physics and Complex Systems team, CPT Marseille (former) Stochastic Systems and Signals group, DTU Nanotech (former)
doc. dr Mladen Amović is an Associate Professor at the Department of Geodesy within the Faculty of Architecture, Civil Engineering and Geodesy at the University of Banja Luka. His academic career includes roles such as Visiting Assistant Professor and Senior Researcher. He specializes in geoinformatics, big data management, and spatial data systems. Education: Advanced degrees in geodesy and related fields (not explicitly detailed in text). Research Interests: Smart city data systems, remote sensing applications, GIS for cadastral systems, and geospatial policy compliance. His work focuses on spatiotemporal data analysis, big data frameworks, and geospatial infrastructure. Recent publications address smart city challenges, disease epidemiology, and agricultural monitoring systems. He has led projects like the 'Central Geospatial Database Analysis' and contributed to initiatives aligning with EU INSPIRE Directive. His research includes collaborations on flood prediction, mineral resource detection, and cadastral portal development. Notable projects include the 'Dokumentovanje arhitektonskog kulturnog nasljeđa' project funded by the BiH Ministry of Civil Affairs and the 'Decarbonization of Energy Sector' initiative.
Silvia Miksch is a Full Professor of Visual Analytics at the Vienna University of Technology (TU Wien), leading the Research Unit Visual Analytics (E193-07) and coordinating the Research Focus on Visual Computing and Human-Centered Technology. She holds a PhD from TU Wien and has held academic roles at institutions like Stanford University (FWF postdoc), Danube University Krems (2006–2010 as University Professor), and TU Wien. Her research focuses on visualization, visual analytics, interaction design, and temporal data analysis with applications in medical informatics, process engineering, and cultural heritage. Education: Master of Social and Economic Science (University of Vienna, 1987), PhD (TU Wien, 1990). Former roles include Chair of the Austrian Society for Artificial Intelligence (ÖGAI) and leadership in EU projects like VALCRI and KAVA-Time. She has authored over 200 publications and received awards such as the IEEE VGTC Visualization Technical Award (2023) and induction into the IEEE VGTC Visualization Academy (2020). Research interests include knowledge-assisted visual analytics, task-driven guidance systems, and spatiotemporal data exploration. She oversees the Laura Bassi Centre of Expertise 'CVAST' and advises numerous PhD and master’s students. Her work bridges theory and practice, with notable projects like the Marvel Cinematic Universe infographic (GD 2019 Best Creative Challenge) and Game of Thrones character networks (GD 2018 Third Prize). Key Awards: Best Paper Award at vis4dh 2019, IEEE VGTC Technical Award 2023 Editorial Roles: Associate Editor of Transactions on Visualization and Computer Graphics (2011–2015), Editorial Board of Journal of Biomedical Informatics (2012–2020) Leadership: Chair of EuroVis Steering Committee (2023–2027), Member of VIS Executive Committee (2015–2020)
Lukas Schrangl is a Researcher at the Institute of Biophysics within the Department of Natural Sciences and Sustainable Resources at the University of Natural Resources and Life Sciences, Vienna (BOKU). His work focuses on biophysical techniques to study molecular interactions, particularly in immunological contexts. His educational background includes a doctoral degree, with his thesis "Quantifying conformational dynamics of biomolecules via single-molecule FRET" completed in 2020. His research spans experimental physics, light optical microscopy, and biophysics, with strong emphasis on software development and data science applications in biophysical research. Schrangl's research interests center on single-molecule FRET techniques to investigate T-cell receptor-ligand interactions and molecular force measurements . His work bridges biophysics, immunology, and computational methods, developing innovative approaches to quantify receptor-ligand interaction times and forces at the molecular level. He has created several open-source software tools including the sdt-python package and fret-tester to advance analysis capabilities in single-molecule biophysics. His publication record shows consistent high-impact output from 2017 through 2025, with recent work focusing on synaptic force shielding in T cell receptor interactions and advanced quantification of receptor-ligand interaction lifetimes. His research demonstrates strong interdisciplinary connections between physics, biology, and computational science. Schrangl actively presents his work at major conferences, including the 69th Annual Meeting of the Biophysical Society (2025) and the Biophysics Austria Conference (2024), demonstrating ongoing engagement with the international scientific community. His technical expertise spans both experimental biophysics and computational methods, making significant contributions to the development of quantitative approaches for studying molecular interactions in immunological contexts.
Nils Moosdorf serves as Professor for Coastal Hydrogeology at Kiel University and Work Group Leader for Submarine Groundwater Discharge at the Leibniz Center for Tropical Marine Research (ZMT) in Bremen, Germany. He also holds an Adjunct Professor position at Southern Cross University in Australia and was a Temporary Member of the Graduate Faculty at the University of Alabama, USA. His work focuses on the critical interface between terrestrial and marine systems through groundwater pathways. 2019: Professor for Coastal Hydrogeology, Kiel University May 2019: Habilitation at University of Bremen 2014-present: Leader of the research group 'Submarine Groundwater Discharge', Leibniz Center for Marine Tropical Research 2009-2014: Researcher, Institute for Biogeochemistry and Marine Chemistry, University of Hamburg 2006-2009: Ph.D. Student, Institute of Applied Geosciences, TU Darmstadt 2000: Diploma in Geology, RWTH Aachen Moosdorf's research primarily investigates submarine groundwater discharge and its role in global biogeochemical cycles. His work spans coastal hydrogeology, groundwater-ocean interactions, and data-driven approaches to understanding Earth systems. He has made significant contributions to understanding how terrestrial groundwater influences marine nutrient cycles, carbon fluxes, and coastal ecosystem health. His research often combines field measurements with modeling approaches to address questions at local to global scales, particularly focusing on how human activities and climate change impact these critical land-ocean interfaces. Analysis of Moosdorf's recent publications reveals a strong focus on coastal hydrogeological processes, particularly submarine groundwater discharge and its biogeochemical implications. His work spans multiple disciplines including hydrogeology, marine biogeochemistry, and climate science, with increasing attention to climate change impacts on coastal systems and potential geoengineering solutions like ocean alkalinity enhancement. The research demonstrates a progression from fundamental process studies toward applied questions of environmental management and climate mitigation. Hermann-Credner Award of the German Geological Society (2017) As an active researcher, Moosdorf serves as Associate Editor for both 'Frontiers in Earth Sciences' and the 'Hydrogeology Journal.' He participates in numerous review activities for international funding agencies including the Israel Ministry of Science and Technology, National Science Foundation, and Netherlands Organisation for Scientific Research. His collaborative network spans dozens of institutions worldwide, reflecting the international nature of coastal and marine research. While specific grant details aren't provided in the text, his extensive publication record suggests successful funding across multiple projects. Moosdorf leads the Working Group on Submarine Groundwater Discharge at the Leibniz Center for Tropical Marine Research, which appears to be a multidisciplinary team investigating the hydrological, chemical, and ecological aspects of land-ocean groundwater connections. His research involves field studies across diverse coastal environments including tropical islands, temperate coastlines, and estuarine systems, often incorporating both natural and anthropogenic influences on groundwater discharge processes.
Khuloud Jaqaman is an Associate Professor at the University of Texas Southwestern Medical Center with dual appointments in the Department of Biophysics and Lyda Hill Department of Bioinformatics. She also participates in the Biomedical Engineering - Computational Biology graduate program and Molecular Biophysics graduate program, reflecting her interdisciplinary approach bridging physics, biology, and computational sciences. Dr. Jaqaman's educational background includes a B.Sc. in Physics (summa cum laude) from Birzeit University (1994-1998), a Ph.D. in Biophysics from Indiana University Bloomington (1998-2003), followed by a postdoctoral fellowship in Cell Biology at The Scripps Research Institute (2003-2009). She served as an Instructor in Systems Biology at Harvard Medical School from 2009-2012 before joining UTSW. Her research focuses on the spatiotemporal organization of cell surface receptors, the mechanisms underlying this organization, and its consequences for cell signaling. The Jaqaman Lab combines physics, biophysics, cell biology, and computational approaches to study these phenomena. They utilize light microscopy, particularly single-molecule and super-resolution imaging, to monitor molecular behavior in native cellular environments, while developing innovative computer vision and machine learning approaches to quantitate observed behaviors beyond visual perception. Analysis of Dr. Jaqaman's publication record from 2015-2021 reveals a consistent focus on receptor organization, single-molecule imaging techniques, and computational analysis methods. Her work spans multiple biological systems including endothelial cells, T cells, and nuclear structures, with applications in immunology, cell signaling, and cellular architecture. The interdisciplinary nature of her research is evident in publications spanning top journals in cell biology, biophysics, and bioinformatics.
