Dr. Maarten Löffler is an Assistant Professor at Utrecht University's Information and Computing Sciences department within the Science faculty. He is also currently serving as a Visiting Professor at Tulane University. His research bridges theoretical computer science with practical applications in geometric algorithms, game research, and data science. Education : PhD in Geometric Uncertainty (Utrecht University), Post-Doc in Social Network Analysis (University of California, Irvine) His expertise lies in computational geometry, discrete mathematics, and algorithm design, with applications in graph drawing and geogaming. He contributes to the Game and Media Technology and Informatica study programs, teaching courses like Three-Dimensional Modeling. Contact: Buys Ballotgebouw, Princetonplein 5, Room BBL411, 3584 CC Utrecht, Netherlands. Phone: +31 30 253 6759.
Prof. Marc van Kreveld is a Professor and Head of the Department of Computer Science at Utrecht University since February 2023. His research focuses on computational geometry, geometric algorithmics, and their applications in GIScience, cartography, and puzzle design. He leads the Geometric Computing group and has made significant contributions to algorithms for trajectory data, geometric similarity, and spatial data analysis. Education: PhD in Computer Science from Utrecht University (1992). Research Interests: Computational geometry, GIScience, graph drawing, LIDAR point cloud reconstruction, and geometric puzzle analysis. His work bridges theoretical foundations and real-world applications, such as route data analysis and environmental modeling. Publications: Over 290 peer-reviewed papers, including foundational work on Fréchet distance algorithms, geometric spanners, and trajectory grouping. Recent contributions include advancements in collision detection for modular robots and mobility data science. Awards & Editorial Roles: Editor-in-Chief of Computing in Geometry and Topology , and editorial board member of Journal of Computational Geometry . Active in program committees for conferences like GIScience and SoCG. Teaching: Specializes in computational geometry and its applications, with a focus on algorithm design and geometric computing. Labs & Teams: Leads the Geometric Computing group at Utrecht University, collaborating on projects like braided river network modeling and automated puzzle generation.
Bettina Speckmann is a full Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU Eindhoven), where she leads the Applied Geometric Algorithms group. She holds additional appointments as EAISI Health Professor and EAISI Foundational Professor, and is affiliated with the Data Science Center Eindhoven. Her research bridges theoretical algorithm design with practical applications in spatial computing. Her research interests lie primarily in computational geometry and geometric algorithms, with strong applications in GIScience, Smart Mobility (including moving object analysis and automated cartography), geo-visualization, visual analytics, and e-Humanities. She focuses on developing efficient algorithms and data structures for spatial data, combining rigorous theoretical methods with practical engineering for real-world impact. Her recent publications (2025) show a strong trend in geometric data processing, particularly in polycube segmentations, dual loop algorithms, density estimation for moving groups, and topological analysis using merge trees and Fréchet distances. These works reflect her interdisciplinary focus on computational geometry, visualization, and data structures. Scientific awards received include: Netherlands Prize for ICT Research (2011) NWO Vici Award (2012) PEriTiA Prize (2020) Bettina Speckmann has advised numerous students and researchers through her group and has secured major grants, including the NWO Vici. She has served in leadership roles such as PC co-chair for Graph Drawing (GD 2011), PC chair for ICALP Track A (2015), and PC co-chair for SoCG (2018). She teaches courses such as Data Structures and Heuristic Algorithms. She leads the Applied Geometric Algorithms group, which actively collaborates with industry partners like HERE Global B.V., Fugro NL Land B.V., and OCLC B.V., and contributes to UN Sustainable Development Goals in areas related to data and mobility.
Till Miltzow is an Assistant Professor in the Department of Algorithms and Complexity at the Faculty of Science, Utrecht University. His research primarily focuses on computational geometry, algorithms, and complexity theory, with particular expertise in the existential theory of the reals (ER) and its applications to geometric problems. Dr. Miltzow has established himself as a leading researcher in computational geometry, particularly known for his work on the Art Gallery Problem, where he and his collaborators proved the problem is ER-complete. His research spans a wide range of topics including geometric embeddings, Hausdorff distance computations, token swapping problems, and the complexity of various geometric decision problems. His research interests include: Computational Geometry and Algorithm Design Complexity Theory, particularly the Existential Theory of the Reals (ER) Geometric Embeddings and Representations Art Gallery Problems and Polygon Guarding Computational Topology and Shape Analysis Algorithmic Game Theory Dr. Miltzow's publications demonstrate a consistent focus on establishing the computational complexity of geometric problems, often showing ER-completeness for problems previously thought to be NP-hard. His work bridges theoretical computer science with practical geometric applications, contributing significantly to our understanding of the boundaries between tractable and intractable problems in computational geometry. Among his notable achievements is the proof that the classic Art Gallery Problem is ER-complete, which resolved a long-standing open question about the problem's complexity. His research has been published in top-tier venues including the Journal of the ACM, SIAM Journal on Computing, and proceedings of major conferences like FOCS and SoCG. Dr. Miltzow maintains an active research program with numerous collaborations across Europe and has made significant contributions to understanding the complexity landscape of geometric problems. His work has implications for computer graphics, robotics, and computer vision, where geometric decision problems frequently arise.
Britta Ricker serves as an Assistant Professor in the Environmental Sciences department at Utrecht University's Copernicus Institute of Sustainable Development. Her expertise spans Geographic Information Science, Remote Sensing, Cartography, and Open Science practices, with active leadership as the Netherlands representative to the International Cartographic Association where she chairs the Commission of Cartography and Sustainable Development. Her research focuses on democratizing geospatial technologies through interactive visualization techniques and low-cost tools, specifically targeting United Nations Sustainable Development Goals (SDG) indicator data mapping. She co-authored the open-access textbook Mapping for a Sustainable World and utilizes Earth Observation satellite data for environmental monitoring across scales from small island states to global systems. Current projects emphasize accessible SDG data representation and innovative cartographic methods for sustainability challenges. Dr. Ricker mentors students in applied geospatial projects including solar potential analysis in data-poor urban environments and citizen science biodiversity monitoring. She regularly lectures at international forums including United Nations agencies (UN-GGIM, ECLAC, UN Women), academic institutions like the University of Bayreuth, and industry conferences such as the Geospatial World Forum.
Kevin AB Verbeek is an Assistant Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e), affiliated with the Applied Geometric Algorithms group and EAISI Foundational program. His research bridges theoretical computational geometry with practical applications in information visualization, graph drawing, and spatial data analysis. Education: PhD in Algorithms for Cartographic Visualization, Eindhoven University of Technology, 2012 Postdoctoral Researcher, UC Santa Barbara, 2012-2014 Verbeek specializes in computational geometry with applications spanning information visualization, automated cartography, social network analysis, and computational topology. His work emphasizes algorithm stability for dynamic data visualization, ensuring minor input changes yield proportionally minor output variations. Current projects include the NWO-funded Veni project on geometric algorithm stability and the GlamMap initiative for GLAM (Galleries, Libraries, Archives, Museums) metadata visualization, addressing real-world challenges in spatial data representation. His publication trends reveal consistent contributions to algorithm stability, hierarchical data visualization, and network analysis, with significant impact in treemap stability, flow map design, and river network modeling. These works demonstrate cross-disciplinary applications from cultural heritage to earth sciences. Scientific Awards: NWO Veni Award (2015) for "Stable Geometric algorithms" project Verbeek coordinates the bachelor honors track "Competitive Programming and Problem Solving" within TU/e Honors Academy and teaches courses including Heuristic Algorithms and Competitive Programming. He serves on the Eindhoven Young Academy of Engineering and contributes to research projects funded by NWO, with ongoing work focused on foundational algorithmic spatial data analysis through EAISI. As core faculty in the Applied Geometric Algorithms group, he actively develops tools for dynamic data visualization and maintains strong collaborations with institutions like UC Santa Barbara, focusing on translating theoretical geometry into practical visualization frameworks for evolving datasets.
Kevin Verbeek is an Assistant Professor in the Applied Geometric Algorithms group at Eindhoven University of Technology (TU/e), affiliated with the EAISI Foundational research institute. His research focuses on computational geometry, information visualization, and algorithms for cartographic challenges. He holds a PhD from TU/e (2012) and conducted postdoctoral research at UC Santa Barbara (2012–2014). He coordinates the TU/e Honors Academy's 'Competitive Programming and Problem Solving' track and is a member of the Eindhoven Young Academy of Engineering. Education: PhD in Applied Geometric Algorithms, TU Eindhoven (2012) Postdoctoral Researcher, UC Santa Barbara (2012–2014) Research Interests: Algorithmic stability for dynamic data visualization Geometric algorithms for social networks and cartography Topological data analysis and computational topology Braided river network modeling Key Projects: NWO Veni Award-funded project on stable geometric algorithms (2015–present) GLAMMap: Interactive geo-visualization for cultural heritage metadata Teaching & Outreach: Coordinator of Honors tracks in Competitive Programming Instructor for courses like 'Heuristic Algorithms' and 'Computer Science Research Project' Awards: NWO Veni Award for 'Stable Geometric Algorithms' (2015) Labs/Teams: Active in EAISI Foundational, focusing on algorithmic spatial data analysis and foundational AI research.
Alessio Arleo is an Assistant Professor at the Eindhoven University of Technology (TU/e) within the Mathematics and Computer Science department, specializing in the Visualization group and Visual Analytics for Data Science . He holds a PhD in distributed computing and graph drawing from the University of Perugia (2018), followed by postdoctoral research at Vienna University of Technology's Visual Analytics unit. His work focuses on temporal network visualization, information diffusion modeling, and distributed graph algorithms. Research interests include temporal networks , interactive visual analytics , and explainable graph drawing . Notable projects include TimeLighting (space-time cube visualization) and XGD (explainable graph drawing frameworks). Recent publications address guidance strategies in visual analytics, healthcare data visualization, and AI-driven graph layout transparency. He teaches the Seminar Visualization course and has co-authored over 30 peer-reviewed articles since 2014. No ancillary activities are listed, and his work is supported by grants from WWTF, FFG, FWF, and SANE.
Kevin A.B. Verbeek is an Assistant Professor in the Applied Geometric Algorithms group within the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). He is also affiliated with the EAISI Foundational program at the Eindhoven Artificial Intelligence Systems Institute. His work bridges theoretical computational geometry with practical applications in information visualization and geospatial data analysis. His research interests focus on computational geometry and its applications, particularly in information visualization. Key areas include graph drawing, automated cartography, social network analysis, computational topology, and the stability of geometric algorithms. His NWO-funded VENI project specifically investigates how to measure and analyze algorithm stability where small input changes should produce small output variations, crucial for visualizing dynamic data. He also contributes to the GlamMap project developing interactive tools for visualizing GLAM (Galleries, Libraries, Archives, Museums) metadata. Analysis of his publication record shows consistent contributions to computational geometry and visualization, with emphasis on stability analysis, treemaps, network visualization, and geospatial applications. His work demonstrates strong connections between theoretical foundations and real-world implementations, particularly in environmental modeling and social network analysis. NWO Veni Award: Stable Geometric algorithms (2015-07-28) Verbeek supervises research projects and coordinates the bachelor honors track 'Competitive Programming and Problem Solving' within the TU/e Honors Academy. His teaching includes courses on heuristic algorithms and research projects. As a member of the Eindhoven Young Academy of Engineering, he contributes to interdisciplinary initiatives. His research has practical applications in geographic information systems, environmental modeling, and cultural heritage data visualization through projects like GlamMap.
