جستجوی استاد راهنمای دانشگاهی

Basile Sauvageمشاهده پروفایل

استاد

• Computer Graphics
• Procedural Textures
• Geometry Processing
• +۵ مورد دیگر

Basile Sauvage is a Professor of Computer Science at the University of Strasbourg and Head of the Computational Geometry & Computer Graphics team at the ICube laboratory. He leads the CS group at the IREM of Strasbourg and holds executive roles in French academic societies (SIF, AFIG) and CNRS research groups. His research focuses on procedural textures, rendering, geometry processing, and virtual reality applications. He has supervised multiple PhD students and led projects like ANR ReProcTex and ASTex. Education: PhD in Applied Mathematics (2005, INP-Grenoble), accredited to supervise research (2018), and certified for higher education teaching (2018). Research interests include texture synthesis, radiance modeling, and multiresolution analysis. Recent work emphasizes real-time procedural textures and distortion correction in graphics. His publications span Eurographics, Siggraph Asia, and Pacific Graphics, with awards including the Best Paper Award at JFIG 2023 and a Graphics Replicability Stamp. He collaborates on scientific mediation projects, such as the AI exhibition at Le Vaisseau. Teaching roles include managing the CS department at the University of Strasbourg’s UFR Mathématique-Informatique. He advises on education policy as part of the Vice-President’s mission for AI-era education. Current PhD supervision includes Arthur Delon (co-advisor) and Romain Fournier. He actively promotes computer science outreach through unplugged activities like 'The Busy Cook' educational module.

Jean-Michel DISCHLERمشاهده پروفایل

استاد

• Computer Graphics
• Texture Synthesis
• Procedural Modeling
• +۴ مورد دیگر

Jean-Michel Dischler is a full Professor of Computer Science at the University of Strasbourg, affiliated with the ICUBE Lab (UMR CNRS-UDS 7357). He leads rendering and visualization research activities within the Department of Computer Science at the Faculty for Mathematics and Computer Science. His academic roles include former leadership of the Computer Science department, vice-director of LSIIT Lab (until 2008), and joint-director of the 3D Computer Graphics Group in ICUBE (until 2018). He has organized major conferences like Eurographics 2014 and EGSR/HPG 2019, and chaired the Eurographics association since 2021. Research focuses on texture synthesis, procedural modeling, 3D acquisition, and high-performance graphics. Key projects include the ASTex C++ library for texture generation. His work bridges procedural and data-driven methods, addressing challenges like non-stationary textures and real-time rendering of complex materials. He has contributed to Eurographics committees, journals, and professional governance, including a decade on the EG professional board. Scientific Awards: Fellow of the Eurographics Association Grants & Projects: INRIA CALVI project (2010), ASTex library development Labs/Teams: ICUBE Lab (3D Graphics Group), former LSIIT Lab Future Work: Continued innovation in procedural texture synthesis and real-time graphics

• Computer Vision
• Deep Learning
• Point Cloud Processing
• +۳ مورد دیگر

ABOUELAZIZ Ilyass is a Researcher-Lecturer at CESI, specializing in Computer Sciences. He holds a PhD from Mohammed V University (2014-2020) and a Master's in Computer Sciences and Telecommunications (2012-2014). His research focuses on Point Cloud Processing, Mesh Quality Assessment, Deep Learning, Building Information Modeling, and Computer Vision. He currently supervises PhD candidate Hafsa Benallal on Point Cloud Segmentation and Denoising for BIM. PhD Topic: No-reference mesh visual quality assessment using deep learning and visual saliency Master's Topic: Computer Sciences and Telecommunications Teaching activities include courses on Algorithms, Web Development, Programming (C, JAVA, Python), Artificial Intelligence, and Image Processing at 2nd to 5th-year engineering levels. He employs active pedagogy, lectures, and practical sessions (TP/TD). Scientific contributions include 20+ peer-reviewed publications in venues like IEEE Access, Pattern Recognition, and conferences such as ICIP and SITIS. He serves as a reviewer for Optics Express and IEEE ICIP, and has organized sessions at ATSIP (2017), SETIT (2016-2017), and URAC Day (2015). Research highlights include pioneering work on graph-based deep learning for mesh quality assessment and developing outlier-removal techniques for point clouds. His work bridges computer vision with sustainable energy solutions, such as photovoltaic prediction and building decarbonization. Future projects emphasize BIM integration with deep learning for smart building applications and enhancing 3D mesh quality metrics using novel neural architectures.

Lucile Hauteمشاهده پروفایل

مدرس

• Biodesign
• Biomaterials
• Non-human Interactions
• +۴ مورد دیگر

Lucile Haute is a Lecturer in Design and Director of the Faculty of Design at Nîmes University, with an associate researcher role at EnsadLab (PSL). She holds a doctorate in visual arts from Jean Monnet University (Saint-Étienne). Her research focuses on biodesign, biomaterials, non-human interactions, and digital publishing methodologies, advocating a research-creation approach. She leads the PROJEKT research unit at Nîmes University and collaborates with SACRe (Paris Sciences et Lettres). Current projects include the 'web to print' library and deanthropocentric care initiatives exploring bioprocesses and fermentation. She co-heads the Design Degree program, coordinating the Biodesign and Digital option. Editorial roles include co-editing .able, Hybrid journal, and directing the liteʁal collection. Past roles include ATER positions, Labex Arts-H2H collaborations, and leadership in projects like 'Hyperfiction Air Duct'. Education: Doctorate in Visual Arts (Jean Monnet University) Research Interests: Biodesign, community economies, digital publishing, hybrid methodologies Projects: Workshops on biomaterials (2022–2025), web to print library, interdisciplinary collaborations Awards: None explicitly listed, though her work has received institutional support (e.g., Labex ICCA, Leonardo/Olats) Advising/Grants: Supervised research-creation projects, led initiatives like Digital Archives of Nicolas Schöffer Labs/Teams: PROJEKT, SACRe, EnsadLab’s Reflective Interaction group

• Knowledge Representation
• Artificial Intelligence
• Computer Science
• +۶ مورد دیگر

François De Bertrand De Beuvron is a Lecturer at INSA Strasbourg, teaching modules such as JAVA Programming, UML Modeling, Databases, Graphic Interfaces, and Logic and AI. He is affiliated with the Shared Knowledge Department and contributes to the Theoretical Bioinformatics, Data Mining and Stochastic Optimization (BFO) team at the Laboratory of Image Sciences, Computer Science and Remote Sensing (LSiiT), University of Strasbourg (UdS). His research focuses on hybrid knowledge representation combining description logics with real-world applications in design, configuration, diagnosis, and classification. Key projects include semantic interpretation of satellite imagery through geographic ontologies and applying TRIZ theory to innovative design via CAD semantic modeling. He emphasizes lifecycle analysis of products, integrating functional, structural, behavioral aspects like maintainability and recyclability. Publications are listed on the LSiiT laboratory's website. No specific awards, grants, or advising activities are detailed in the provided text.

Sahar Husseiniمشاهده پروفایل

پژوهشگر ارشد

• Deepfake Detection
• Computer Vision
• Biometrics
• +۵ مورد دیگر

Sahar Husseini is a Research Fellow at EURECOM's Digital Security department. Her research focuses on deepfake detection, face verification, and cybersecurity. She has contributed to evaluating deepfake generators using frameworks like MetaHumans and 3D-assisted methods, addressing challenges such as beautification filters and spoofing attacks. Her work spans computer vision, biometrics, and machine learning, with publications at top conferences like ICCV, ICASSP, and ICIP. She collaborates with experts like Jean-Luc Dugelay on topics ranging from authentication systems to signal processing. Her thesis emphasizes strengthening face authentication in the deepfake era. Research Interests : - Developing robust methods against deepfake spoofing attacks. - Enhancing face verification models via adaptive alignment techniques. - Investigating the impact of image filters on deepfake detection. - Leveraging 3D data and MetaHumans for generator evaluation. - Optimizing CNN models for small datasets in color constancy tasks. - Exploring optical flow for object tracking. Key Contributions : - Introduced RAW data's critical role in effective deepfake detection. - Proposed AlignFace for pose/expression/illumination adaptation. - Demonstrated vulnerabilities of detectors to beautification filters. - Created frameworks for quantitative head motion replication analysis. - Authored a comprehensive deepfake generator evaluation benchmark. Labs/Teams : Active member of EURECOM's Digital Security research group, working on cutting-edge AI security solutions.

• Image Processing
• Mathematical Analysis
• Computer Vision
• +۳ مورد دیگر

Jean-Michel Morel is a Chair Professor in Imaging at City University of Hong Kong and a Professor at École Normale Supérieure Paris-Saclay. His career spans roles as a PhD student at Université Paris IV, postdoc at SISSA (Trieste), teaching assistant at Université de Marseille, and assistant professor at Université Paris Dauphine. He has held visiting positions at Universitat Illes Balears, UCLA, and Duke University. His research focuses on mathematical foundations of image analysis, algorithm development, and applications in satellite imaging, computer graphics, and art theory. He co-invented widely used image denoising algorithms deployed in over 700 million cameraphones via DxO Labs. He founded Image Processing Online (IPOL), a journal enabling reproducible algorithmic research with 15 university collaborators and 500,000+ experiments. Industrial collaborations include French Space Agency (CNES), Planet, Huawei, AFP, Kayrros, Tarkett, and Chow Sang Sang. His team secured €1.1M/year in funding from 2013-2023 through grants and contracts. Key awards include the CNRS innovation medal (2015) and a 2018 honorary doctorate. Current research explores mathematical models for perceptual image classification, computational art theories using computer graphics, and synthesizing abstract textures/shapes. His work bridges pure mathematics with applied image science, emphasizing reproducibility and industrial impact.

Stéphane Conversyمشاهده پروفایل

استاد

• Human-Computer Interaction
• Computer Science
• Participatory Design
• +۵ مورد دیگر

Stéphane Conversy is a Professor at the Laboratoire d'Informatique de l'Aviation Civile (LII) within ENAC (École Nationale de l'Aviation Civile) in Toulouse, France. He holds a HDR (Habilitation à Diriger des Recherches) in Informatics from the University of Toulouse (2013), a PhD in Computer Science from Université de Paris-Sud (2000), and an MSc in Computer Science from the same institution (1995). His research focuses on Human-Computer Interaction (HCI), Participatory Design, and the science of controlled transformations in interactive systems. He leads the Interactive Informatics Team and co-directs the MSc Computer Science - HCI program. Key areas of expertise include interactive architecture design (e.g., MDPC framework), latency measurement in interfaces, and visualization techniques for air traffic control (ATC). His work bridges theoretical computer science with practical applications in aviation, healthcare, and collaborative systems. Notable contributions include the Volta electric helicopter project and interactive cockpit systems research. Publications span interactive system design, programming language semantics, and safety-critical interfaces. He has pioneered concepts like picking views and inverse transformations in graphical systems, influencing both academic theory and industrial applications.

• Applied Mathematics
• Statistics
• Machine Learning
• +۳ مورد دیگر

Stéphanie Allassonnière is a Professor in Applied Mathematics and Statistics at the School of Medicine, Université Paris Cité. She serves as Vice-President for Research Economic Transfer and Industrial Partnerships at the same university and holds a PR[AI]RIE fellowship as deputy director. As co-founder of Sonio, she bridges academic research with industrial applications. Her research focuses on interdisciplinary applications of statistics and machine learning in medical imaging and health data analysis. Her work spans computational statistics, Gaussian graphical models, and stochastic optimization, with a strong emphasis on translating methodological advances into clinical and biomedical solutions. Her scientific contributions have been recognized through the PR[AI]RIE fellowship and her inclusion in Computer Vision News' 'Women in Science' feature. She supervises PhD and Master’s students, many of whom are engaged in industry-academia collaborations like CIFRE programs with Implicity and GE Healthcare. She leads research team 22 at the Cordeliers Research Center (UMRS 1138) and has taught advanced courses such as Computational Statistics (MVA Master 2), Medical Data Analysis (M2 Bioentrepreneur), and MCMC methods at institutions including Université Paris Descartes, École Polytechnique, and Université Paris Dauphine.

Julien Chiquetمشاهده پروفایل

مدرس پاره‌وقت

• Statistics
• Machine Learning
• Sparse Methods
• +۱۰ مورد دیگر

Julien Chiquet is a researcher and part-time lecturer at École Polytechnique (2020-2024), and the head of the UMR MIA Paris-Saclay research unit. He is affiliated with AgroParisTech on the Paris-Saclay campus and leads the SOLsTIS team. He serves as the chief editor of the journal Computo , focusing on computational statistics and data science. Education: Habilitation (2015) Research Interests: His work bridges statistical methodology and life sciences, with a focus on developing and applying advanced statistical methods such as sparse models, multivariate analysis, and optimization techniques. Key areas include dimension reduction in high-dimensional count data, probabilistic graphical models, and applications in ecology, genomics, and metagenomics. He emphasizes reproducible research practices, recently developing a Quarto template for HCERES reports integrating LaTeX and Pandoc. Recent Contributions: Recent work includes advancements in the Poisson lognormal model, stability selection via the sharp R package, and Python tools like pyPLNmodels for analyzing multivariate count data. His research often addresses challenges in ecological network inference, scRNA-seq analysis, and genomic prediction. Labs & Teams: Based at UMR MIA Paris-Saclay, he contributes to the SOLsTIS team, advancing computational methods for biological data analysis. The lab relocated to the new Palaiseau campus in 2022, fostering interdisciplinary collaborations.

• Programming Languages
• Formal Methods
• Compilers
• +۳ مورد دیگر

François Pessaux is a Lecturer in the Computer Science and Systems Engineering Unit (U2IS) at ENSTA ParisTech. He specializes in programming languages, formal methods, and compiler design, with a focus on topics such as type systems, formal verification, and hybrid systems simulation. His work includes contributions to the FoCaLiZe framework for formal integrated development environments and the analysis of critical software systems. Education & Teaching: Teaches courses such as Algorithms and Programming (IN101), Advanced C Language (IN102-MPI), Around Logic (IN103-MPI), and Principles of Programming Languages and Compilation (IN213). Research Interests: His research spans programming language semantics, formal methods for software verification, and the design of tools for critical systems. Notable areas include: Formal specification and verification techniques using FoCaLiZe. Type-based analysis for exception handling and dependency management. Hybrid systems simulation through projects like Zélus and DynIbex. Publications: Over 12 key publications since 1997, including seminal work on FoCaLiZe, type systems, and exception analysis. Labs/Teams: Active contributor to the FoCaLiZe project and related formal methods initiatives.

Stéphane Rivièreمشاهده پروفایل

استادیار

• Computer Science
• Algorithmic Geometry
• Computer Graphics
• +۳ مورد دیگر

Stéphane Rivière is an Assistant Professor in Computer Science at Université Joseph Fourier (Grenoble I). He holds a PhD in computer sciences from the same institution, completed in 1996 under the supervision of Claude Puech, focusing on visibility computation in 2D polygonal scenes. His research interests include algorithmic geometry, computer graphics, and image synthesis. Education: École Polytechnique (1989-1992), Master in Computer Science, Mathematics, and Applications (1992-1993), PhD in Computer Science (1993-1996). His expertise spans programming languages (Pascal, C++, Java), algorithmic foundations, and object-oriented programming. He has taught introductory computer science courses and object-oriented programming at Université Joseph Fourier. During his PhD, he was part of the iMAGIS research team under Michel Pocchiola and later Claude Puech. No scientific awards or grants are explicitly listed, though his thesis work demonstrates strong research engagement. Leisure activities include skiing and hiking.

David Cazierمشاهده پروفایل

استاد

• Virtual Reality
• Computer Graphics
• Computational Geometry
• +۴ مورد دیگر

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.

Rémi Allègreمشاهده پروفایل

دانشیار

• Geometric Modeling
• Appearance Modeling
• Texture Synthesis
• +۶ مورد دیگر

Rémi Allègre is an Associate Professor in Computer Science at the Institute of Technology Haguenau (IUT Haguenau), affiliated with the University of Strasbourg (France). He conducts research at the ICube CNRS laboratory within the Geometric and Graphical Computing (IGG) group. Department: Multimedia and Internet Professions (Internet and multimedia technologies) Research Lab: ICube - UMR 7357, CNRS Contact: remi.allegre@unistra.fr | +33 (0)3 88 05 34 39 His research focuses on Geometric Modeling , Appearance Modeling , and Texture Synthesis , with applications in 3D data processing, procedural modeling, and biomedical imaging. Key trends include: Developing differentiable point process models for inverse procedural modeling Creating GAN-based data augmentation techniques for histopathological images Advancing semi-procedural texture synthesis methods Improving dynamic surface reconstruction algorithms Investigating hybrid representations (implicit surfaces, meshes, point sets) Multiscale label-map extraction for structured texture synthesis Scientific recognition includes: AFIG 2005 Best Article Award He supervises doctoral students such as Pascal Guehl, Florian Allender, Guillaume Baldi, Steve de Rose, and Maximilien Nowak. Collaborations span the ICube laboratory and biomedical imaging projects.

Charline Grenierمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Procedural Patterns
• 3D Modeling
• +۳ مورد دیگر

Charline Grenier is a researcher affiliated with the IGG Team (Geometric and Graphics Computing) at the iCube laboratory, Université de Strasbourg. Her work focuses on procedural generation, computer graphics, and real-time rendering. She completed her PhD in computer graphics under Prof. Basile Sauvage (2020–2023) and holds a Master's in International Computer Science (University Clermont-Auvergne, 2020) and an engineering diploma from ISIMA (Clermont-Ferrand, 2020). Education: PhD in Computer Graphics, Université de Strasbourg (2020–2023) Master ICS, University Clermont-Auvergne (2020) Engineering diploma, ISIMA (2020) Her research emphasizes procedural micro-pattern generation and real-time terrain enhancement. Key projects include ReProcTex and publications in Pacific Graphics and Computer Graphics Forum. She has received awards for student presentations and posters. Awards: Best student presentation award, Pacific Graphics 2022 Best poster, MSII Strasbourg doctoral school 2022 Teaching includes supervising 3 M1 students (2021) and lecturing on Applied Numerical Analysis (L2, 2022). She actively engages in scientific outreach, including interventions at the Strasbourg Science Museum and participation in the Science Festival.