Frédéric Demoly is an Associate Professor at the University of Bourgogne Franche-Comté (UBFC) and affiliated with the Université de Technologie de Belfort-Montbéliard (UTBM) in France. He is based at the Laboratoire Interdisciplinaire Carnot de Bourgogne (ICB UMR CNRS 6303) and leads a research group focused on formalism, methods, and tools for proactive design of adaptable and transformable products. His role involves advanced research and teaching in mechanical design and additive manufacturing.
Martin-Pierre Schmidt is a Lecturer at the National Institute of Applied Sciences (INSA) Rouen, affiliated with the Department of Mathematical Engineering. His research focuses on topological/multi-physics optimization, approximation theory, and applications in computer-aided geometric design (CAGD). He completed his PhD in March 2020 under the supervision of Christian Gout, with co-supervisors David Bonner and Auxkin Ortuzar from Dassault Systèmes, funded by Dassault Systèmes. His work integrates machine learning and data science into imaging and design processes. He teaches in the GM5 program at INSA Rouen, emphasizing machine learning and data approximation techniques. His research team is part of the Numerical Analysis, Imaging and Approximation group. Notable contributions include interactive topology optimization tools, biomimetic microstructure design, and robust 3D shape detection algorithms. His thesis defense in 2020 involved a jury of international experts in mechanical engineering and computational design. Key collaborations include Dassault Systèmes, with applications in CAD model optimization and manufacturing process design. His work bridges theoretical optimization methods with practical industrial applications in additive manufacturing and structural engineering.
Francesco De Pace is a PostDoc Researcher at the Institute of Visual Computing and Human-Centered Technology within the Faculty of Informatics at Vienna University of Technology (TU Wien). His research focuses on the intersection of augmented reality, virtual reality, and human-robot interaction, with particular emphasis on developing innovative interfaces for industrial applications. Dr. De Pace's research spans several key areas in immersive technologies and human-computer interaction. His primary interests include Augmented Reality (AR) and Virtual Reality (VR) systems, Human-Robot Interaction (HRI), Brain-Computer Interfaces (BCIs), and advanced tracking and localization techniques. He has made significant contributions to the development of AR/VR interfaces for industrial robots, outdoor tracking with Real-Time Kinematic GPS, and SLAM (Simultaneous Localization and Mapping) systems. His work bridges theoretical research with practical industrial applications, focusing on creating more intuitive and effective human-machine interfaces. Dr. De Pace's recent publications demonstrate a clear trajectory toward enhancing human-robot collaboration through immersive technologies. His research shows increasing sophistication in integrating multiple modalities (visual, spatial, and neural) to create more natural interaction paradigms. A notable trend is the application of AR/VR to industrial settings, particularly for assembly tasks, path planning, and training scenarios. His systematic evaluation of RTK-GPS for wearable AR represents important foundational work for outdoor AR applications, addressing critical challenges in positional accuracy across different environmental conditions. While specific awards are not prominently documented in the available information, Dr. De Pace's research has been supported by significant funding mechanisms, including grants from the Austrian Research Promotion Agency (FFG) under Grant Agreement No FO999886342 KIRAS MRespond, indicating recognition of the importance and potential impact of his work. Dr. De Pace appears to be actively involved in multiple research projects, including PostDisaster and MRespond as indicated in his profile. His collaborative approach is evident through his extensive co-authorship with researchers across institutions. While specific student advising information isn't detailed in the available materials, his role as a PostDoc Researcher likely involves mentoring junior researchers and contributing to the academic development of students working on related projects. Dr. De Pace is associated with the Mixed Reality Lab at TU Wien, as indicated in the website navigation. His research appears to be conducted within collaborative frameworks that include both academic and industry partners. His work on the MRespond project suggests engagement with emergency response applications of mixed reality technologies, indicating interdisciplinary team involvement spanning computer science, engineering, and potentially public safety domains.
David Cazier is a **Professor at the University of Strasbourg** and a **Researcher at the ICube Laboratory**, specializing in geometric and graphical computing. He also teaches computer science at the **IUT of Haguenau**. His research focuses on three main axes: multiresolution geometric models, real-time interaction in virtual reality, and tools for adapting such models to simulations and visualization. His work bridges theoretical advancements in geometric modeling with practical applications in medical imaging, crowd simulation, and augmented reality. **Research Interests**: Cazier’s expertise includes virtual reality (VR) immersion, real-time interaction techniques, and the development of efficient geometric models for complex simulations. His projects often involve hierarchical meshes, topological changes during deformations, and applications in surgical AR. Key areas include multiresolution representations, collision detection in dynamic environments, and non-manifold geometry processing. **Publications**: His recent work emphasizes medical applications (e.g., surgical AR with topological changes) and foundational contributions to geometric data structures (e.g., CGoGN, CPH). He explores user interaction challenges in the digital divide era and develops tools for crowd simulation using deformable agents. **Collaborations and Projects**: Active in collaborations with the ICube Lab’s IGG team, Cazier contributes to platforms like CGoGN and InVirtuo. His research spans national and European projects, including IHU, ANR, and CNRS initiatives. He supervises internships on geometric models for VR applications and interdisciplinary projects combining geometry with medical and industrial challenges.
Pascal Schreck is a Professor of Computer Science at the University of Strasbourg, affiliated with the Department of Computer Science within the UFR of Mathematics and Computer Science. He is a researcher at the ICube laboratory and has held administrative roles, including Director of the Computer Science Department (2008–2011) and course coordinator for specialized programs. His research focuses on geometric computing, formal methods in geometry, automated deduction, and geometric constraint solving, with contributions to theorem proving, computational geometry, and CAD applications. His work integrates algebraic and geometric approaches to solve problems like constructibility in geometric constructions, incidence geometry, and constraint systems. He has developed methods using Coq proof assistants for formal verification and explored topics such as homotopy-based solutions for geometric constraints. His contributions span theoretical advancements and practical applications in areas like 3D modeling and medical trajectory planning. Key research trends include leveraging formal systems (e.g., Coq) for mechanized proofs, analyzing geometric constructs' feasibility, and improving algorithms for constraint resolution. His publications address foundational geometry theorems (e.g., Dandelin-Gallucci), combinatorial geometry, and automated construction verification. He has also contributed to international workshops and conference proceedings on automated deduction in geometry. As a member of the ICube laboratory and the IGG Team (Geometric and Graphical Computing), Schreck collaborates on interdisciplinary projects, bridging mathematics, computer science, and engineering. His work emphasizes rigorous formalization, algorithm optimization, and practical implementation in geometric problem-solving domains.
Marios Pattichis is a Professor of Electrical and Computer Engineering at the University of New Mexico (UNM), serving as Director of Online Programs since 1999. He leads the Image and Video Processing and Communications Lab (ivPCL) and co-founded Cosmiac. His work focuses on biomedical image analysis, video analytics for clinical decision support, and educational technology initiatives like the AOLME project targeting underrepresented middle-school students. Pattichis holds 10 patents, over 80 journal papers, and $15.9M in research funding from NSF, NIH, and AFRL. Education: Ph.D. and M.S. in Computer/Electrical Engineering from UT Austin (1998, 1993), with dual B.A./B.Sc. in Mathematics and Computer Sciences (1991). Research Interests: Biomedical CAD systems, explainable AI in imaging, dynamically reconfigurable architectures, and bilingual STEM education. His lab develops tools for stroke risk assessment via carotid ultrasound, solar coronal hole segmentation, and classroom activity analysis to measure student participation. Awards: 2022 EAMBES Fellow for contributions to biomedical image analysis. Editorships include IEEE Transactions on Image Processing and IEEE Signal Processing Letters. Grants & Teams: Directed over $15.9M in grants, advised numerous students (though none listed explicitly), and collaborates with educators on AOLME's integrated math/CS curricula. Active in codec comparisons for healthcare video streaming (VVC vs. AV1) and FPGA-based image processing acceleration. Labs/Initiatives: ivPCL (medical imaging/video systems); DRASTIC (adaptive video processing); ESTRELLA (bilingual STEM outreach). Involved in IEEE journal special issues on video analytics and multilingual education.
Kai Hormann is a full professor in the Faculty of Informatics at Università della Svizzera italiana (USI Lugano). He earned his Ph.D. in computer science from the University of Erlangen-Nürnberg in 2002 and has held positions at Clausthal University of Technology, Caltech, and the CNR in Pisa. His research focuses on mathematical foundations of geometry processing, including barycentric coordinates, subdivision algorithms, and rational interpolation. Hormann has authored over 100 publications and serves as an associate editor for journals like Computer Aided Geometric Design and Dolomites Research Notes on Approximation . In 2024, he received the prestigious John A. Gregory Award for his contributions to geometric modeling. Education : Ph.D. in Computer Science, University of Erlangen-Nürnberg (2002) Diploma in Mathematics, University of Erlangen (1997) Abitur, Leibniz-Gymnasium Bad Schwartau (1992) Research Interests : Hormann’s work bridges computer science, applied mathematics, and engineering. His current projects include interactive shape deformations, time-dependent object processing, 3D visualization, and GPU-accelerated algorithms. His research areas encompass geometry processing, computational sciences, and numerical analysis. Publications : His recent articles focus on barycentric coordinates, subdivision schemes, and surface reconstruction. Themes include transfinite coordinates, curvature continuity, and efficient interpolation methods. Awards : John A. Gregory Award (2024) Chair of SIAM Activity Group on Geometric Design (2017–2018) Advising & Grants : He has advised numerous PhD students, including work on barycentric rational curves and subdivision schemes. He has organized conferences such as the SIAM GD and GMP series, reflecting his leadership in computational geometry. Labs & Teams : Hormann is affiliated with the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI), collaborating on interdisciplinary projects in AI and geometry processing.
Ioanna Lykourentzou is an Associate Professor at Utrecht University, leading the Collaborative Technologies Lab and coordinating Computing Science Master's and Information Sciences Honors Bachelor's programs. She holds a PhD and ECE degree from the National Technical University of Athens. Her research focuses on collaborative systems, combining computational science (machine learning, optimization) with social sciences (team dynamics, personality assessment). Education background includes a PhD and ECE degree from National Technical University of Athens. She has held postdoctoral and visiting roles at Carnegie Mellon University, INRIA Nancy-Grand Est, and Henri Tudor. Research interests span computational team formation, Human-AI collaboration, and cultural heritage accessibility. Recent work includes projects on GenAI in education (NWO Take-off grant), algorithmic team formation for game development (EU MSCA funding), and ethical AI frameworks. Active in open science initiatives as an Open Software Fellow and Ethics Review Board member. Key collaborations include MIT-Netherlands Seed Fund projects on Human-AI design, and interdisciplinary work in digital humanities through Utrecht's AI in Cultural Inquiry SIG. Her lab hosts researchers like Pedro Zambon (MSCA fellow) and Heleen Kerstholt (AI-enabled teamwork).
Tomas Lindehell is a Lecturer at the Umeå Institute of Design (UID), part of Umeå University, specializing in 3D modeling, visualization, and digital fabrication. He teaches tools like Autodesk Alias, Blender, and Keyshot, and oversees prototyping workflows involving milling and 3D scanning. A recognized university teacher, he received the Faculty of Science and Technology's pedagogical prize in 2012 and was recognized as a teacher in 2023. Education: Master of Science in Engineering (Hydraulic and Pneumatics) from KTH Royal Institute of Technology (1990) Research & Teaching Focus: Lindehell emphasizes hands-on learning with 3D software and prototyping technologies. His expertise spans NURBS modeling, polygon modeling, and advanced visualization techniques. He integrates tools like SolidWorks for surface modeling and photogrammetry for 3D scanning. His courses bridge theoretical design principles with practical manufacturing processes. Awards: 2012: Pedagogical Prize from Faculty of Science and Technology, Umeå University 2023: Recognised Teacher Award Advising & Labs: Lindehell oversees milling operations using CAM software and supports rapid prototyping initiatives. His work with Audi UNIverse showcased UID students' design concepts to industry leaders. He maintains active involvement in UID's hands-on fabrication facilities, including laser scanning and 3D-printing workflows.
Dr. Maria Helenowska-Peschke is an Associate Professor at the Department of Visual Arts, Faculty of Architecture, Gdańsk University of Technology. Her research focuses on parametric design, digital fabrication, and the integration of technology in architectural education. She holds a PhD in arts studies (1999) and a habilitation in engineering (2018). Her work explores the impact of digital tools on architectural practice, including energy modeling for sustainable housing and blended learning methodologies. Notable publications include analyses of parametric design trends, energy-efficient housing, and digital workshop innovations. She leads projects like the 'Parametric-Algorithmic Paradigm in Architecture' funded by MNiSW grants. Teaching focuses on computer techniques and hybrid educational models. Contact: mhelen@pg.edu.pl, Office: Gmach Główny - room 353.
Ismail Rakip Karas is a Professor of Computer Engineering and Head of the 3D GeoInformatics Research Group at Karabuk University, Turkey. He holds a BSc from Selcuk University (1997), MSc from Gebze Institute of Technology (2001), and PhD from Yildiz Technical University (2007). His career includes roles as Visiting Researcher at Universiti Teknologi Malaysia (2010–2014) and Research Assistant at Gebze Institute of Technology (2000–2009). Currently, he serves as Deputy Rector of Karabuk University and has held administrative positions including Dean of Safranbolu Fine Art and Design Faculty, Director of Safranbolu Vocational School, and acting Dean of the Faculty of Architecture. Research interests span GeoInformatics, 3D GIS, network analysis, spatial data structures, and intelligent transportation systems. He has led over 20 national/international projects, including EU-funded initiatives and collaborations with institutions like Nara Institute of Science and Technology and University of Szeged. His work emphasizes smart city applications, indoor navigation, and emergency evacuation models. Publications include over 100 peer-reviewed articles and book chapters, focusing on GIS applications, machine learning in geospatial analysis, and 3D modeling. He has organized conferences like Geo-Advances 2017 and serves on editorial boards of journals such as the International Journal of Geo-Spatial Knowledge and Intelligence.
Asst. Prof. Kristína G. Rypáková is an Assistant Professor in the Department of Architecture at the Academy of Fine Arts and Design in Bratislava. Her work focuses on integrating digital technologies into architectural education and practice. She teaches courses such as Virtual Studio, Mathematics and Geometry in Architecture, Digital Rendering/Modelling, and Digital Fabrication using robotic laboratory/CAM systems. Her research interests emphasize computational design methodologies, parametric modeling, and advanced fabrication techniques. She actively contributes to the intersection of architecture, technology, and art through her teaching and academic projects. No scientific awards or articles are explicitly mentioned in the provided text. She oversees courses related to digital tools and robotic fabrication but no specific grants or student advisement details are listed.
Dr. Xi Zou is a Lecturer in Aerospace Engineering at Swansea University since May 2023. He holds a PhD from the University of Pavia and Polytechnical University of Catalonia via the Erasmus Mundus Joint Doctorate fellowship. Previously, he worked as a postdoctoral researcher at the University of Nottingham and a Stress Engineer at Airbus China. His expertise includes finite element methods, mesh generation, reduced order modelling, and composite structures analysis. Education: BSc in Spacecraft Design (Beihang University), MSc in Mechanics (Beihang University), PhD in Engineering (Erasmus Mundus Joint Doctorate) His research focuses on advancing numerical methods for structural analysis, particularly in composite materials and airframe structures. Recent work includes developing NURBS-enhanced finite element meshes and efficient damage hotspot identification tools. He has published widely in journals like Computer-Aided Design and International Journal for Numerical Methods in Engineering. Dr. Zou has supervised MSc projects exploring expandable space modules using origami principles. He actively collaborates with industry and teaches modules such as Engineering Mathematics and Finite Element Analysis.
Dr. Feng Ju is an Associate Professor and Program Chair of Industrial Engineering at the School of Computing and Augmented Intelligence, Arizona State University (ASU). He joined ASU in 2015 and holds additional roles as a Senior Global Futures Scientist at the Julie Ann Wrigley Global Futures Laboratory. His research focuses on stochastic modeling, optimization of production systems, additive manufacturing, healthcare delivery systems, and battery management for electric vehicles. He is affiliated with IEEE, IISE, and INFORMS, and serves as an associate editor for multiple journals. Dr. Ju has received numerous awards, including the Dr. Hamed K. Eldin Outstanding Early Career IE Award and SME Outstanding Young Manufacturing Engineer Award. He advises students in Industrial Engineering and collaborates on projects funded by NIST, Boeing, and NSF. Education: Ph.D. Industrial and Systems Engineering from University of Wisconsin-Madison; M.S. Electrical and Computer Engineering from UW-Madison; B.S. Electrical and Computer Engineering from Shanghai Jiao Tong University. Additional training includes a visiting scholar position at Carnegie Mellon University’s Robotics Institute. Research Interests: Stochastic modeling of production systems, semiconductor manufacturing, healthcare logistics, machine learning in additive manufacturing, and battery management systems. His work emphasizes real-time control, simulation optimization, and smart manufacturing integration. Awards: Over 15 honors including Best Paper Awards at IEEE CASE, IISE Transactions, and NIST competitions. Mentored students in winning hackathons and competitions, including ASME-CIE Hackathon 2021 and Tesla Factory collaborations. Service: Organized conferences including IEEE CASE 2019 and served as track chair for IISE Annual Conference 2019. Active in editorial roles for IISE Transactions and IEEE Robotics and Automation Letters. Labs: Leads the Manufacturing and Service Automation Lab, focusing on interdisciplinary research in smart manufacturing, healthcare systems, and sustainable production.
Chi-Wing FU, Philip is a Professor in the Department of Computer Science and Engineering at The Chinese University of Hong Kong (CUHK). He holds dual roles in research and education, including Associate Editor-in-Chief of IEEE Computer Graphics and Applications. His research focuses on computer graphics, 3D vision, and human-computer interaction, with over 100 publications in top venues like SIGGRAPH, CVPR, and IEEE Visualization. Education: B.Sc. (1st Hons), Computer Science & Engineering, CUHK M.Phil., Computer Science & Engineering, CUHK PhD, Indiana University, Bloomington Research Interests: Dr. Fu's work spans 3D shape generation, computational LEGO design, AR visualization, and robotic interaction. He has pioneered projects like Make-A-Shape (large-scale 3D modeling) and DreamStone (text-driven 3D creation). His team also develops tools for medical data visualization and hand-object pose estimation. Recent Trends in Articles: Recent work emphasizes AI-driven creativity (e.g., LEGO art, text-to-3D systems) and real-time AR applications. His publications often bridge theory (e.g., generative models) with practical systems (e.g., user interfaces for design). Awards: Postgraduate Research Output Award (2023) MSRA Fellowship Nomination (2022) Best Associate Editor (IEEE CG&A) Outstanding Reviewer (ICCV 2021, CCF CAD/CG 2023) Advising & Grants: Supervised over 40 PhD/Master students and postdocs. Active in securing grants for projects like computational LEGO design (with Autodesk), medical AR visualization, and 3D generative AI. Collaborates with industry partners like Adobe and Huawei. Labs & Teams: Leads the Computational Design and Visualization Lab, focusing on 3D systems, robotics, and creative AI. Key projects include the LEGO Sketch Art toolchain and the HandShadowPoser AR system.
