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James BrockmoleView profile

Professor

• Visual Attention
• Visual Memory
• Gaze Control
• +3 more

James Brockmole is a Professor and Department Chair at the University of Notre Dame’s College of Arts and Letters. His research bridges visual attention, memory, and spatial cognition, with a focus on how gaze control and embodied cognition influence perception. He has held leadership roles including Associate Dean for the Social Sciences and Editor-In-Chief of Psychonomic Bulletin & Review . Brockmole earned his Ph.D. from the University of Illinois at Urbana-Champaign and completed a postdoctoral fellowship at Michigan State University. His work employs eye-tracking methodologies to study real-time cognitive processes, particularly in dynamic environments. Research interests include the interplay between attention and memory, the impact of aging on visual cognition, and the role of tool use in spatial perception. His lab’s interdisciplinary approach addresses questions like how attentional biases affect learning and decision-making, and how technological interventions (e.g., gaze-based systems) can mitigate mind wandering in educational settings. Recent work explores the cognitive mechanisms underlying art perception, human-AI interaction, and the neural correlates of statistical learning. Articles highlight trends in mind wandering detection, math anxiety’s impact on attention, and the computational modeling of gaze behavior during scene viewing. His contributions to cognitive science have advanced methodologies in visual cognition and shaped educational technology design.

Stefan GumholdView profile

Professor

• Computer Graphics
• Visualization
• Medical Imaging
• +3 more

Professor Stefan Gumhold is a leading academic in computer graphics and visualization at TU Dresden. He has held roles including Head of the Chair for Computer Graphics and Visualization since 2005 and served as Dean of the Faculty of Computer Science from 2010 to 2012. His expertise spans visualization techniques, medical imaging, and immersive technologies. Gumhold earned his Ph.D. in 2000, focusing on mesh compression, and later received a Dissertation Award in the same year. He has contributed to projects like the Heisenberg Scholar Research Group and led the Kommission Umwelt at TU Dresden. His teaching includes courses such as Introduction to Computer Graphics, Data Visualization, and Scientific Visualization. Gumhold’s research emphasizes visualization platforms (e.g., ISAAC), image fusion, and neural network applications in medical diagnostics. His work often integrates virtual reality for data analysis, as seen in tools like VRCellLabeler and ExtremeWeatherVis. Education: Diploma in Computer Science (University of Tübingen, 1998), M.Sc. in Applied Physics (University of Massachusetts Boston, 1996). Research Highlights: Development of visualization frameworks, 3D reconstruction, and invertible neural networks for outlier detection. Awards: Dissertation Award 2000. Grants & Labs: Leadership in TU Dresden’s Computer Graphics lab and contributions to collaborative research projects like Fast-Haptic.

• Neuroimaging
• Functional Magnetic Resonance Imaging (fMRI)
• Brain Connectivity
• +3 more

Vince Calhoun, PhD, is a Research Professor at Yale School of Medicine. His research integrates neuroimaging, machine learning, and neuroscience to study brain connectivity in disorders like Alzheimer's disease and schizophrenia. He earned his MS from Johns Hopkins University (1996) and PhD from the University of Maryland (2002). Research Focus: Dr. Calhoun's work centers on developing advanced fMRI analysis methods, including dynamic functional connectivity and multimodal MRI techniques. His interests span neuroinformatics, brain network modeling, and AI-driven diagnostics for neurological and psychiatric conditions. Recent Publications: His 15 latest articles (2024-2025) focus on machine learning applications in neuroimaging, such as federated learning for data privacy, graph neural networks for intelligence mapping, and predictive modeling of cognitive decline. Key themes include explainable AI, neurodevelopmental disorders, and cross-modal data fusion.

• Statistics
• Machine Learning
• Environmental Data Analysis
• +3 more

Nikolaus Umlauf is an Associate Professor at the Department of Statistics, University of Innsbruck. He specializes in Bayesian distributional regression, structured additive models, and spatiotemporal analysis, with applications in public health, climate science, and real estate valuation.

Mark HillView profile

Lecturer

• Digital Humanities
• Computational Social Science
• Intellectual History
• +5 more

Mark Hill is a Lecturer in Digital Humanities, specializing in the intersection of digital methods, computational social science, and intellectual history. His work emphasizes social network analysis, public discourse analysis using large datasets, and critical evaluations of digital research tools. Current projects explore idea transmission across historical and contemporary contexts. Education: BA in Political Science, Concordia University MSc in Political Theory, LSE PhD in Rousseau's Political Thought, University of Oxford Research focuses on: Quantitative text analysis and NLP Ethical considerations in AI and digital research Early Modern European intellectual networks Recent work includes studies on football fandom's digital impact, occupational prestige scales via LLMs, and drug policy dynamics. His scholarship bridges historical and computational methodologies, addressing both substantive research topics and methodological innovation. Notable contributions include analyzing historical book formats and metadata's role in reconstructing intellectual networks. His work frequently intersects with debates on digital humanities' ethical frameworks and the evolution of cultural concepts like 'Europe.'

• Geomatics
• Cultural Heritage Digitization
• 3D Modeling and Reconstruction
• +7 more

Francesca Matrone is a Fixed-term Assistant Professor in the Department of Environment, Land and Infrastructure Engineering (DIATI) at Politecnico di Torino, Italy. Her work bridges geomatics, artificial intelligence, and cultural heritage conservation, with a focus on 3D modeling, GIS, and HBIM integration for urban and historical environments. Her research interests include Geomatics, Cultural Heritage Digitization, AI in Geospatial Analysis, Drone-Based 3D Modeling, Semantic Segmentation of Point Clouds, and Smart Cities . She applies advanced technologies like UAVs, deep learning, and BIM-GIS integration to enhance the documentation, maintenance, and resilience of built heritage. The recent publications highlight a strong trend in using AI and machine learning for semantic segmentation of 3D heritage models, integration of HBIM with GIS using standards like IFC and CityGML, and drone-based photogrammetry for urban and territorial planning. These works reflect a multidisciplinary approach combining computer science, civil engineering, and digital heritage. Francesca Matrone is actively involved in research projects such as: HERITALISE (2025–2028, EU-funded): Digitization and cloud visualization of heritage buildings ACLIMO (2024–2026): Research collaboration with APAM on protected areas COGNITIO-FORT (2025–2026): Scientific Director for a project with Unione Montana Valle Stura She teaches across multiple programs: PhD : GeoAI for advanced urban analyses; Drones for 3D modeling (Main Teacher) Master’s : GIS Modeling for City and Land; Knowledge of Built Heritage under Climate Change Bachelor’s : GeoAI: Artificial Intelligence and Geospatial Data; Topography (Course Collaborator) She is a member of the Teaching Colleges for Civil and Building Engineering and Electronic, Telecommunications and Physics Engineering. She also holds a Learning to Teach (L2T) Open Badge from Politecnico di Torino, demonstrating her commitment to pedagogical excellence. Francesca is a co-inventor of the MAIN10ANCE PLATFORM , a national software patent aimed at enhancing the maintenance and conservation of historical built heritage through integrated HBIM-GIS systems.

M. Ángeles SerranoView profile

Research Professor

• Complex Networks
• Network Science
• Multiplex Networks
• +9 more

M. Ángeles Serrano is an ICREA Research Professor at the Universitat de Barcelona, where she conducts interdisciplinary research in complex systems and network science. Her work bridges physics, biology, and economics through the study of complex networks and their real-world applications. Research Interests: Her primary focus lies in complex networks , including multiplex networks , networks of networks , and time-varying connectivity . She applies these frameworks to diverse systems such as molecular networks in cells, international trade, and socio-technological infrastructures. Her research emphasizes structural and dynamic properties of interconnected systems, aiming to uncover universal principles across domains. The most recent publications reflect a consistent trend in advancing theoretical and applied aspects of network science, particularly in multiscale modeling, visualization, and interdisciplinary applications. Her work integrates physics-based approaches with data-driven analysis across biological, economic, and social contexts. Scientific Awards: Outstanding Referee Award, American Physical Society Advising and Grants: While specific students are not listed, her leadership roles suggest active mentorship. She is a founding member of Complexitat , the Catalan network for complex systems, and a promoter of the UBICS (Universitat de Barcelona Institute of Complex Systems), indicating involvement in large-scale collaborative research initiatives and likely grant-funded projects. Labs and Teams: She is closely associated with UBICS and has collaborated internationally through institutions such as Indiana University, EPFL, and IFISC, suggesting integration into major research consortia focused on complexity science.

Claire Wyatt-SmithView profile

Professor

• Educational Assessment
• Teacher Education
• Digital Learning Assessment
• +5 more

Claire Wyatt-Smith is Professor of Educational Assessment and Literacy and Director of the Institute for Learning Sciences and Teacher Education at Australian Catholic University (ACU). She also serves as Director of the Research Centre for Digital Data and Assessment in Education at ACU. Her leadership extends to major national initiatives including the Graduate Teacher Performance Assessment (GTPA) across 19 Australian higher education institutions. Professor Wyatt-Smith's research focuses on assessment standards, professional judgment, and the implications of digital disruption for teacher professionalism. Her work addresses critical issues in initial teacher education, assessment and learning analytics, human judgment and moderation practices, language and literacy education, and digital assessment. She has examined assessment through research, practice, and policy lenses with extensive cross-domain collaborations. Her recent publications reveal significant trends toward AI integration in educational assessment, post-pandemic assessment practices, teacher judgment development, and the intersection of large-scale and classroom assessment. These works demonstrate her focus on how digital technologies reshape assessment practices while maintaining attention to equity, professional judgment, and standards implementation across diverse educational contexts. 2020 European e-Learning Excellence Awards (second place) ACU Vice-Chancellor's Staff Excellence Medal (2018) Australian Council for Educational Leaders Queensland Honorary Fellowship (2015) Research Excellence Award, Griffith University Griffith University Arts, Education and Law Faculty Group Award (2012) As a Full HDR Supervisor, Professor Wyatt-Smith has secured substantial research funding from the Australian Research Council (including multiple Discovery and Linkage projects from 2011-2025), national and state governments, and international educational agencies. Her major projects include the ARC-funded study on teacher judgment of student samples, the GTPA initiative across six Australian states, and the NAPLAN review involving multiple Australian jurisdictions. She has published extensively in leading international journals and with major academic presses including Routledge, Sage, and Springer, where she serves as Foundation Editor for two book series. Professor Wyatt-Smith leads the Research Centre for Digital Data and Assessment in Education, which focuses on digital learning assessment, big data, and learning analytics. Her team collaborates with education authorities across Australian states and territories, industry partners, and international organizations including UNESCO on projects addressing assessment standards, teacher professionalism, and digital disruption in education.

Peter UhrigView profile

Professor

• Digital Linguistics
• Big Data in Linguistics
• Corpus Linguistics
• +12 more

Peter Uhrig is a Professor at the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), holding the Chair of Digital Linguistics with a Focus on Big Data within the Institute of English and American Studies. He is based in Erlangen, Germany, and actively contributes to research and teaching in computational and cognitive linguistics. His research interests lie at the intersection of linguistics, computation, and cognition, with a strong emphasis on corpus-based analysis , construction grammar , multimodal communication , and digital methods in language research . He investigates phenomena such as collocation, argument structure, creativity in language, and spoken word comprehension using large-scale datasets and advanced computational models. His recent publications reveal a clear trend toward interdisciplinary, data-intensive research. He frequently collaborates on projects involving multimodal corpora , gesture analysis , spoken language processing , and computational modeling , often in collaboration with researchers from computer science and cognitive neuroscience. His work is published in leading journals in linguistics and cognitive science. How Collostructional Analysis Contributes to the Description of Argument Structure Constructions with Slots for that-and Infinitive Clauses (2024) The pluralization palette: unveiling semantic clusters in English nominal pluralization through distributional semantics (2024) World Futures through RT’s Eyes: Multimodal Dataset and Methodology (2024) Prof. Uhrig has co-edited several academic volumes and plays a key role in developing research infrastructure, such as the Red Hen Protocol for anonymizing audiovisual data and tools for multimodal analysis. While specific grant funding is not detailed, his involvement in large collaborative projects indicates active grant-supported research. He also contributes to academic service through editorial work and conference organization. He is involved in building digital infrastructure for multimodal research, including work on gesture retrieval systems and data anonymization protocols. His lab or research group appears to focus on integrating computational tools with linguistic theory, particularly within the framework of construction grammar and cognitive linguistics.

• Internet of Things (IoT)
• Smart Grids
• Renewable Energy Systems
• +3 more

Mohamed A. Ahmed is a researcher affiliated with Central Michigan University, School of Engineering & Technology , with additional collaborations across institutions like Ain Shams University, Memorial University of Newfoundland, and Prince Sultan University. His work spans interdisciplinary domains including Internet of Things (IoT) Smart Grids Renewable Energy Systems Machine Learning Recent research focuses on IoT platforms for smart energy management , including electric vehicle charging infrastructure, remote elderly care systems, and large-scale wind turbine monitoring. He has contributed to wireless network architectures for cyber-physical energy systems and developed fuzzy logic algorithms for EV charging prioritization. Publications highlight expertise in time-series forecasting for energy demand, clustering algorithms for smart grid planning, and data aggregation techniques in wind energy applications. Collaborations frequently involve researchers such as Young-Chon Kim, Ali Mohamed Eltamaly, and José Luis Gallardo.

• Computational Fluid Dynamics (CFD)
• Turbulence Simulation
• Wind Farm Optimization
• +5 more

Professor Sylvain Laizet is a faculty member in the Department of Aeronautics at Imperial College London, part of the Faculty of Engineering. He holds a PhD and Habilitation à Diriger des Recherches from the University of Poitiers in France, specializing in Computational Fluid Dynamics (CFD). His research focuses on turbulent flows and their engineering applications, including wind farm optimization, quantum algorithms for fluid mechanics, and machine learning integration in CFD. Key research areas include: Wake-to-wake interaction in wind farms Bayesian optimization for drag reduction and energy efficiency Immersed boundary methods for moving objects Quantum computing for solving PDEs in fluid dynamics His work leverages high-order numerical methods and large-scale simulations, with contributions to frameworks like Xcompact3D and WInc3D. Recent publications emphasize quantum algorithms, turbulence entrainment, and data-driven optimization strategies for renewable energy systems. Scientific contributions span over 50 peer-reviewed articles in top-tier journals, focusing on advancing CFD methodologies and their applications in environmental and industrial fluid mechanics. His team collaborates globally, including partnerships in France and Brazil.

Patrick E. ManteyView profile

Professor

• Signals and Systems
• Image and Signal Processing
• Geographic Information Systems
• +15 more

Professor Patrick E. Mantey is a distinguished faculty member at the University of California, Santa Cruz (UCSC), where he serves in the Jack Baskin School of Engineering. He is the founding dean of the school (1997–2001) and continues to contribute as a professor in Computer Engineering. He also holds leadership roles as Director of the Institute for Networking, Information Systems and Technologies and as the UCSC affiliate director of CITRIS. His career bridges academia and industry, with prior experience at IBM and teaching at Stanford University. Ph.D., Electrical Engineering, Stanford University (NSF Fellow) M.S., Electrical Engineering, University of Wisconsin-Madison B.S., Electrical Engineering, University of Notre Dame (magna cum laude) His research spans signals and systems, with early contributions in digital signal processing, geographic information systems, and database applications. His current focus is on resilient and renewable energy systems through the RREES Lab, where he investigates microgrid energy management, anomaly detection, and federated microgrid systems. His work integrates machine learning, real-time data analysis, and decision support systems. The majority of his recent publications center on real-time environmental monitoring, multimedia systems, and educational technology. Trends show a strong emphasis on distributed systems, data visualization, and networked applications in environmental and educational contexts. His earlier work laid foundations in digital filtering, power systems, and interactive geographic data systems. Fellow of the IEEE (2001) NSF Fellowship during doctoral studies Microsoft, NOAA, NSF, and U.S. Army Corps of Engineers research awards Professor Mantey has advised numerous students through capstone projects and research initiatives, particularly in networked systems and environmental informatics. His research has been supported by major grants from the National Science Foundation, Office of Naval Research, NOAA, and industry partners including IBM, Cisco, Sun, Microsoft, and Hewlett-Packard. He has led large-scale projects such as REINAS and contributed to the development of the UCSC Scientific Visualization Laboratory. He is actively involved in multiple research groups, including the Storage Systems Research Center (SSRC), the Telecollaboration Lab, the Computer Communication Research Group (CCRG), and the CARNIVORE Project. These labs focus on storage systems, educational technology, wireless networks, and environmental sensor networks, reflecting the interdisciplinary nature of his work.

• Computer Science
• Scientific Visualization
• Data Analysis
• +3 more

David H. Rogers is a Researcher affiliated with Los Alamos National Laboratory , specializing in Scientific Visualization and Data Analysis . His work focuses on Exascale Computing , Color Mapping , and In Situ Visualization to enhance large-scale scientific data workflows. His research explores methods for Lossy Data Reduction , 3D Streamline Visualization , and Perceptual Uniformity in Color Sequences . He has contributed to frameworks like VTK-m and CinemaScience , enabling efficient data exploration and domain-specific visualization. David collaborates extensively with institutions such as University of Utah , Oak Ridge National Laboratory , and University of Oregon , addressing challenges in High-Performance Computing and Visual Analytics . His publications highlight interdisciplinary efforts in Computer Graphics , Flow Dynamics , and Scientific Data Management .

Juliane MaiView profile

Academic

• Computational Hydrology
• Hydrological Modeling
• Sensitivity Analysis
• +4 more

Juliane Mai is a Research Associate Professor at the University of Waterloo's Department of Earth and Environmental Science and a former Research Scientist at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig. Her work focuses on computational hydrology, model calibration, sensitivity analysis using high-performance computing, and data dissemination tools like HydroHub and CaSPAr. She develops blended hydrological models that combine multiple process implementations and leads large-scale intercomparison projects (GRIP-E, GRIP-GL) across North America's 3,000+ basins. Her research bridges environmental modeling with machine learning and data science, emphasizing open-access platforms for stakeholders. Key projects: GRIP-E/GRIP-GL model intercomparisons Methodological innovations: xSSA, EEE, MVA sensitivity techniques Created data portals: HydroHub for visualization, CaSPAr for climate data Her 2023 Journal of Hydrology paper outlines calibration strategies for environmental models, while 2022 Nature Communications work quantifies process sensitivities across North America. She received the 2023 ASCE-EWRI best case study award for GRIP-E research and serves on editorial boards like Journal of Hydrology .

Sandro Luigi FioreView profile

Associate Professor

• Data Science
• Big Data
• Scientific Data Management
• +13 more

Sandro Luigi Fiore is an Associate Professor in the Department of Information Engineering and Computer Science at the University of Trento, Italy. He has held academic positions at the University of Salento and visiting scientist roles at the University of Chicago and Lawrence Livermore National Laboratory. His research integrates data science, big data, and high-performance computing with climate informatics and open science. Education: Ph.D. in Innovative Materials and Technologies, University of Lecce, 2004 Master of Science in Computer Engineering (with honors), University of Lecce, 2001 His research interests span Data Science, Big Data, Scientific Data Management, Artificial Intelligence, and Distributed/Cloud/Parallel Computing , with a strong application focus on Climate Change and Open Science . He develops FAIR-enabled data analytics solutions and contributes to large-scale data infrastructures such as ESGF, EOSC-hub, and INDIGO-DataCloud. His work emphasizes provenance, reproducibility, and interoperability in scientific computing. The articles reflect a consistent trajectory in large-scale scientific data systems , evolving from Grid-DBMS and parallel computing to modern applications in climate informatics, AI, and FAIR data. Key themes include distributed data management, middleware, exascale software, and reproducible workflows in HPC environments. Scientific Awards: Earth System Grid Federation Team Award (2017) UNIDATA Community Equipment Award (2011) Best Student Paper Award, ITCC2003 Fiore has advised on and led multiple national and European projects including EOSC-hub, IS-ENES, and BARRACUDA (RDA-Europe3). He actively supports the adoption of FAIR data principles in scientific repositories, advising on data policies, architecture, provenance, and interoperability. He is a member of the FAIR Champions group and serves on the Advisory Board of FAIRsFAIR. He is involved in key research teams and projects such as the Earth System Grid Federation (ESGF) , Globus Lab (University of Chicago) , and PCMDI/LLNL . His work contributes to climate model intercomparison (CMIP5/6) and the development of next-generation data infrastructure for open science.