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B.T. (Tino) Mager is an Associate Professor of History and Theory of Architecture and Urbanism at the University of Groningen's Faculty of Arts . He holds leadership roles as President of ICOMOS Germany and Secretary General of ICOMOS's International Scientific Committee on Water and Heritage. His research focuses on cultural heritage theory, post-war modernist architecture, Japanese architecture, and digital humanities methods. Education: Media Technology (Leipzig) Art History and Communication Science (Berlin, Barcelona, Tokyo) PhD in Cultural Heritage Theory (TU Berlin) Research Interests: Monument conservation and climate adaptation Transnational artist education (19th century) Port-city cultures and water heritage Colonial-era built heritage AI applications in architectural history Teaching: Core courses on architectural history and theory at University of Groningen and TU Delft Summer schools on water heritage and digital methods Awards: 1st Tiburtius Prize for outstanding dissertation (2016) Projects: Time Machine Europe (Big Data for heritage) PortCityFutures (global port-city research) Water and Heritage for Sustainable Development Lab/Team: Leads interdisciplinary teams in digital heritage and water resilience initiatives through the University of Groningen and international collaborations.

• Cultural Heritage Theory
• Monument Conservation
• Post-War Modernist Architecture
• +5 more

M.A. (Maruf) Dhali, Dr. is an Assistant Professor in Artificial Intelligence at the University of Groningen's Bernoulli Institute (Faculty of Science and Engineering) and concurrently holds an Assistant Professor position in the Qumran Institute (Faculty of Religion, Culture and Society). He specializes in machine learning, pattern recognition, and computer vision with a focus on historical document analysis, particularly the Dead Sea Scrolls. His work bridges AI and cultural heritage preservation. Education: Ph.D. in Artificial Intelligence (ERC-funded project on Dead Sea Scrolls), M.Sc. (Distinction) in Computer Vision, Machine Learning & Robotics (Heriot-Watt University, 2015). Additional studies at the Universities of Burgundy (France), Girona (Spain), and Edinburgh (UK). Research Interests: Machine Learning applications in historical document analysis, handwriting recognition, deep learning, and probabilistic robotics. His work has been featured in PLoS ONE , Springer LNCS , and international media including BBC News and The Independent. Grants & Projects: Principal Investigator for NWO HAICu Project (2024-2030) on Dutch cultural heritage data. Formerly part of the ERC-funded Dual-mode Time Axis Calibration project (2016-2021). Awards: Knapp Lecture Scholar at the University of Oxford (2025). Invited speaker at global institutions including KU Leuven, University of Basel, and NTNU. Teaching: Coordinates courses like Pattern Recognition , Deep Learning Practical , and Handwriting Recognition . Co-teaches interdisciplinary modules such as Apocalypse and Politics and The Text Awakens .

• Artificial Intelligence
• Machine Learning
• Pattern Recognition
• +8 more

Dr. Leo Dorst is a Professor at the Informatics Institute within the Faculty of Sciences at the University of Amsterdam. He leads research in geometric algebra and computer vision, and is actively involved in both teaching and international conference organization. His work bridges theoretical mathematics with practical applications in computer science. Dr. Dorst has been instrumental in advancing geometric algebra as a computational framework for geometrical applications. His research spans from foundational mathematical principles to practical implementations in computer vision, robotics, and machine learning. He is particularly known for his work on conformal geometric algebra, plane-based geometric algebra, and their applications to 3D geometry and physics modeling. His research has evolved from theoretical foundations to cutting-edge applications in deep learning and morphological neural networks. Dr. Dorst has authored the influential book "Geometric Algebra for Computer Science" and has been organizing the Applied Geometric Algebras in Computer Science and Engineering (AGACSE) conference series since 2010. His most recent conference, AGACSE 2024, featured presentations on geometric algebra applications in computer graphics, machine learning, physics, and engineering. 2005 Inventor of the Year award Dr. Dorst has supervised numerous thesis projects and has been active in mentoring students through reading clubs on computer vision topics, including studies of Hartley and Zisserman's "Multiple View Geometry" and Kanatani's works. His teaching portfolio includes linear algebra, computer vision, robotics, and applied mathematics courses at various levels from bachelor to PhD. He is a key member of the Computer Vision Group at the University of Amsterdam, where his work connects mathematical theory with practical implementations in imaging, robotics, and machine learning systems.

• Geometric Algebra
• Computer Vision
• Clifford Algebra
• +5 more

Scott Trager is a Professor at the University of Groningen's Faculty of Science and Engineering, affiliated with the Kapteyn Astronomical Institute. His research focuses on stellar populations, galactic evolution, and astronomical instrumentation, particularly through the WEAVE spectroscopic survey. He holds leadership roles including Scientific Director of NOVA and Principal Investigator for the WEAVE project. His work combines observational astronomy with advanced data analysis techniques, including machine learning and dimensionality reduction. Research Interests: Stellar populations and their chemical evolution Galactic mergers and their impact on active galactic nuclei Interstellar medium dynamics in distant galaxies Development of large-scale spectroscopic surveys (e.g., WEAVE) Key Achievements: Received the Best Paper Award (2022) for contributions to data visualization Lead developer of the WEAVE survey instrument Published over 170 peer-reviewed articles, focusing on galactic evolution and observational techniques Labs/Teams: Involved in the WEAVE consortium, 4MOST project, and Kapteyn Astronomical Institute's research groups.

• Stellar populations
• Chemical evolution of galaxies
• Astronomical instrumentation
• +5 more

Sebastiano Vascon is an Associate Professor in the Department of Computer Science at Ca' Foscari University of Venice, with research spanning artificial intelligence, machine learning, and computer vision. His work emphasizes graph-based methods, game theory, and deep learning, applied to cross-disciplinary domains including climate change, environmental science, Polar Science, and cultural heritage restoration. His research integrates theoretical AI advances with real-world industrial applications, focusing on trajectory forecasting, time-series compression, climate risk assessment, and puzzle-based cultural heritage reconstruction. Recent publications reveal a strong trend toward solving complex environmental and archaeological challenges through neural networks, graph theory, and 3D vision, often bridging game-theoretic principles with practical AI deployment. Vascon holds significant academic service roles including Area Chair for CVPR 2025, BMVC 2025, ECCV 2024, and Program Chair for Fusion 2024. He serves as Associate Editor for Frontiers and has chaired major conferences including BMVC (2022-2024) and WACV 2021, demonstrating leadership in the global AI community.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +7 more

Jasper Candel is an Assistant Professor in the Soil Geography and Landscape department at Wageningen University. He holds a MSc in Earth and Environment (Wageningen University) and a PhD in Physical Geography (Utrecht University and Wageningen University). His research focuses on geomorphology, hydrology, and landscape evolution, with an emphasis on nature-based solutions for climate resilience, river restoration, and subsurface stratigraphy. He leads projects such as CASTOR, NAT, RESHAPE, and NL2120, and has received a VENI Grant from NWO (2024) to study peat-river regeneration. Candel teaches courses on Geology, Geomorphology, and Hydrogeology while actively engaging with stakeholders in landscape regeneration initiatives. Education: MSc Earth and Environment (Wageningen University, Hydrogeology specialization) PhD Physical Geography (Utrecht University/Wageningen University, 2019 cum laude) Research Interests: Nature-based climate adaptation strategies River morphology and restoration dynamics Shallow subsurface processes linking soil formation and groundwater flow Palaeohydrological reconstruction of river systems Publications Highlight: Recent work explores river self-constraining mechanisms, Holocene peat dynamics, and fluvial engineering impacts. His 2020 article on low-energy river mobility has been widely cited. Grants & Awards: NWO VENI Grant (2024) for peat-river regeneration research Labs/Teams: Coordinates the Soil Geography and Landscape group at Wageningen, collaborating with interdisciplinary teams on landscape regeneration and geohydrological modeling.

• Geomorphology
• Hydrology
• Soil Geography
• +3 more

Dr. Jelte de Jong is a researcher and Head of the Computer Group at the Kapteyn Astronomical Institute, part of the Faculty of Science and Engineering at the University of Groningen. His work focuses on gravitational lensing analysis, machine learning applications in astronomy, and large-scale survey data processing. He leads computational efforts for projects like the Kilo-Degree Survey (KiDS) and contributes to datasets such as KiDS+VIKING-450 and KiDS-VIKING-450 cosmic shear. His research interests include weak lensing, galaxy evolution, and cosmological parameter estimation through multi-probe analysis. Key contributions include developing automated lens detection algorithms using Deep Learning (e.g., DenseLens) and analyzing galaxy halo properties using weak lensing data. He has published extensively in journals like Monthly Notices of the Royal Astronomical Society and Astronomy & Astrophysics , with a focus on cosmology and astrophysical data analysis. His work often involves collaborations on international surveys and contributes to the Euclid mission's preparatory efforts. Dr. de Jong's datasets and methodologies are widely cited in cosmological studies, emphasizing his role in bridging computational methods with observational astronomy. He holds an academic position at the Kapteyn Institute and actively participates in the astronomy community through research and institutional roles.

• Astronomy & Astrophysics
• Gravitational Lensing
• Machine Learning
• +3 more

Dr. Shoko Jin is a Researcher at the Kapteyn Astronomical Institute within the Faculty of Science and Engineering at the University of Groningen. Her work centers on astronomical instrumentation and galaxy evolution, with no indication of part-time status or additional institutional affiliations. Her research spans: Galaxy formation and evolution dynamics Stellar population analysis and star formation processes Spectroscopic survey design (notably the WEAVE project) Applications of machine learning in astrophysical data analysis High-redshift cosmic structures and gravitational lensing Dr. Jin's publications (2018-2025) show consistent focus on large-scale astronomical instrumentation, particularly the development and optimization of the WEAVE spectrograph. Her collaborative work frequently addresses galaxy surveys, data retrieval methods, and telescope system validation. She is affiliated with the Kapteyn Astronomical Institute but leads no explicitly named research group. Prospective collaborators may contact her via s.jin@rug.nl.

• Astronomy
• Astrophysics
• Galaxy Evolution
• +4 more