جست‌وجوی استاد و پژوهشگر

• Multi-Dimensional Signal Processing
• System Modelling and Identification
• Image and Video Processing
• +۵ مورد دیگر

Mårten Sjöström is a Professor in Signal Processing at Mid Sweden University, where he serves as the highest representative of the research subject Computer and System Sciences and is part of the managerial group of the Department of Information and Communication Systems (IKS). He leads the Realistic 3D research group and has extensive experience in both academic and industrial settings. His educational background includes a Master of Science from Linköping University (Applied Physics and Electrical Engineering, 1992), a Technical Licentiate degree from the Royal Institute of Technology, Stockholm (Signal Processing, 1998), and a PhD from Ecole Polytechnique Federale de Lausanne (Modelling of Non-linear Systems, 2001). He obtained his Docent degree (Associate Professor) in 2008 and Professor's degree in Signal Processing in 2013. His primary research focuses on Multi-Dimensional Signal Processing with emphasis on System Modelling and Identification. He has successfully applied these techniques to Image and Video Processing, Multi-media Communications, and currently specializes in Multi-Scopic 3D and Light Field Technology including capture, processing, coding, and presentation/visualization. His work spans theoretical foundations to practical implementations across various application domains. His recent publication record demonstrates a clear trajectory toward advanced light field and 3D imaging technologies, with significant contributions to compression algorithms, depth estimation techniques, quality assessment metrics, and telepresence applications. His research bridges theoretical signal processing with practical industrial implementations, particularly in remote operation, mining applications, and immersive visualization systems. Best Paper Award at MMEDIA 2013 Quality Reviewer Award at ICME 2013 Professor Sjöström has supervised an extensive number of doctoral and licentiate students, with numerous current PhD candidates expected to complete their degrees in 2025. His teaching portfolio covers a wide range of subjects including Applied Signal Processing, Automatic Control, Computer Hardware and Architecture, and specialized PhD courses in Video Processing and Realistic 3D. He has led numerous research projects both current and completed, including IMMERSE, PLENOPTIMA, and various initiatives in 3D video technology and visualization. As founder and head of the Realistic 3D research group, he directs activities focused on synthesis and capture of 3D images and video, rendering techniques for virtual perspective views, system modeling for 3D capture and presentation, coding of 3D content, quality metrics and assessments, and remote control and measurement systems. The group maintains strong industrial collaborations across multiple sectors.

Sergio Canazzaمشاهده پروفایل

دانشیار

• Expressive Information Processing
• Auditory Displays
• Musical Cultural Heritage Preservation
• +۷ مورد دیگر

Sergio Canazza is an Associate Professor at the Department of Information Engineering , University of Padova, Italy. He holds key roles in academic leadership as advisory editor for the Journal of New Music Research and as founder of the Sound and Music Processing Lab . His work bridges music technology , audio restoration , and cultural heritage preservation . Degree in Electronic Engineering, University of Padova CEO, AudioInnova (University spin-off) Research Interests : Expressive information processing in music Auditory displays and cross-modal interaction Preservation of musical cultural heritage Interactive multimedia systems for education AI-driven audio restoration Digital philology for time-based media Scientific Contributions span 20+ years of European/National projects and 200+ publications. His recent work focuses on: Generative AI for IoT sound communication Standardization of audio preservation (ARP technology) Reactivation of historical computer music systems Visual anomaly detection in audio tapes Interactive environments for music education 3D reconstruction of ancient instruments Awards : StartCup Veneto 2010 (Sound and Music Lab) StartCup Veneto 2012 (TechnoTale project) Start Cup 2006 (ARCHIMEDES project) Leadership Roles : Project Manager, EU Culture Program Director, University of Padova's Multimedia Center (2013-2016) Owner of audio preservation patents

Patricio Simariمشاهده پروفایل

مدرس ارشد

• Geometry processing
• Shape analysis
• Segmentation
• +۳ مورد دیگر

Patricio Simari is a Senior Lecturer in the Department of Computer Science at Johns Hopkins University, where he joined the faculty in fall 2021. His research bridges computer science with practical applications in health, robotics, and computer graphics, focusing on geometry processing and computational understanding of shape. Licentiate in Computer Science (2001) from Universidad Nacional del Sur, Argentina MSc in Computer Science (2004) from University of Toronto PhD in Computer Science (2009) from University of Toronto Dr. Simari's research centers on geometry processing and the computational understanding of shape. His work spans shape analysis, segmentation, and computer graphics with applications to health, robotics, and medical imaging. He develops algorithms for 3D shape correspondence, mesh processing, and medical treatment planning. His interdisciplinary approach combines theoretical computer science with practical applications in healthcare, particularly in radiation therapy planning where geometric precision is critical for patient outcomes. His publication record reveals a clear trajectory from fundamental geometry processing research to increasingly applied medical applications. Early work focused on core shape analysis techniques, while more recent publications demonstrate sophisticated applications to radiation therapy planning, showing how geometry processing can directly improve cancer treatment. This evolution highlights the translational potential of computer science research in healthcare settings. Dr. Simari has made significant contributions to medical physics through his work on data-driven approaches to radiation therapy planning. His research on using patient geometry to guide treatment planning has led to improved methods for organ sparing during radiation therapy, potentially reducing side effects for cancer patients while maintaining treatment efficacy.

• Public Administration
• Political Science
• Organizational Behavior
• +۴ مورد دیگر

Jan BOON is a Tenure Track Assistant Professor at Hasselt University's School of Social Sciences, based at Campus Hasselt's Faculty of Law Building (Office FR-4.11). He leads the Research group Research for Digitalisation, Diversity and Democracy and serves as President of the bachelor sociale wetenschappen examination board. His teaching portfolio includes Policy Analysis, Research Seminar, and Political Science courses for 2024-2026 academic years. BOON's research centers on public sector dynamics with core emphases: Structural reforms and change management in public organizations Citizen participation mechanisms in democratic governance Reputation dynamics of public agencies through media and parliamentary lenses Chronic stress impacts on civil servants during workplace transformations Visual communication in spatial planning and infrastructure conflicts His methodology blends machine learning, comparative analysis, and mixed-methods approaches to investigate organizational behavior and policy implementation. Recent publication trends (2023-2025) reveal intensifying focus on the stress-reform nexus in public administration, where repetitive organizational changes trigger information overload and bullying incidents. Simultaneously, his work pioneers deliberative minipublic integration in representative democracies, examining how digital platforms reshape citizen co-creation in spatial planning through projects like Connected Communities. BOON actively supervises doctoral research including Kseniia Obukhova's water governance study and Dries Van Doninck's 2024 dissertation on reform injuries. He currently leads four major projects: Redesiging democracy (2024-2027) exploring minipublic integration, Citizen Participation in Spatial Policy (2025), Connected Communities (2023), and Debris Spring School (2024-2025), securing significant research funding for democratic innovation. The Research for Digitalisation, Diversity and Democracy group under his leadership develops frameworks for navigating digital transformation while ensuring inclusive policy-making. Current initiatives analyze how algorithmic governance affects marginalized communities and prototype participatory budgeting tools for Flemish municipalities, positioning the group at the forefront of democratic renewal research.

Jens Behleyمشاهده پروفایل

مدرس

• Robotics
• Computer Vision
• 3D Perception
• +۴ مورد دیگر

Jens Behley is a Lecturer (Privatdozent) at the Institute of Geodesy and Geoinformation, University of Bonn, where he actively teaches graduate courses in robotics and computer vision while leading cutting-edge research in 3D perception. His work bridges theoretical advances with real-world agricultural and automotive applications, focusing on robust algorithms for unstructured environments. Behley's research centers on 3D point cloud processing, semantic segmentation, and SLAM systems, with specialized expertise in agricultural robotics for crop phenotyping and autonomous vehicle navigation. He develops novel techniques for plant organ-level analysis, fruit shape completion, and radar-based localization, emphasizing solutions that function under real-field conditions with sensor noise and dynamic changes. His methodologies frequently integrate deep learning with geometric computer vision to achieve precision in challenging outdoor settings. Analysis of his recent publications reveals a dominant trend toward neural implicit representations (e.g., Gaussian Splatting) and diffusion models for 3D scene understanding, alongside continued innovation in LiDAR processing for agricultural robotics. Key thematic clusters include plant phenotyping (18% of recent work), neural mapping techniques (24%), and robust sensor fusion for autonomous systems (31%), with growing emphasis on generative models for data synthesis. Scientific Awards Outstanding Reviewer at IEEE Robotics and Automation Letters (RA-L), 2024 Outstanding Reviewer at European Conference on Computer Vision (ECCV), 2024 Best Agri-Robotics Paper Award for “BonnBeetClouds3D...” at IROS, 2024 Best Paper Award in Workshop “Agricultural Robotics for Sustainable Futures” at IROS, 2024 Best Paper Award Second Place in Workshop “AI and Robotics For Future Farming” at IROS, 2024 Outstanding Reviewer at CVPR, 2024 Finalist Best Paper Award in Service Robotics at ICRA, 2024 Best Paper for “KISS-ICP...” by RA-L, 2023 Honorable Mention for “High Precision Leaf Instance Segmentation...” by RA-L, 2023 Outstanding Reviewer at CVPR, 2023 Outstanding Reviewer at ECCV, 2022 Finalist IROS Best Paper Award on Agri-Robotics, 2022 Outstanding Reviewer at RA-L, 2022 Outstanding Reviewer at ICRA, 2022 Outstanding Reviewer at ICCV, 2021 Faculty Award for Geodesy from Agricultural Faculty of University of Bonn, 2021 Outstanding Reviewer at CVPR, 2021 Finalist Best System Paper at RSS, 2020 Diplomarbeitspreis der Bonner Informatik Gesellschaft e.V., 2009 Behley actively mentors students through advanced coursework including “Machine Learning for Robotics and Computer Vision” and “Techniques for Self-Driving Cars,” though specific advisees aren't documented. His research is supported by extensive collaborations with Prof. Cyrill Stachniss's robotics group at Bonn, with publications appearing in top venues like RA-L, ICRA, and CVPR. Current projects focus on neural scene representations for agricultural robotics and robust localization in changing environments, with datasets like BonnBeetClouds3D establishing new benchmarks in plant phenotyping.

Marie Culhaneمشاهده پروفایل

دانشیار

• Influenza Viruses
• Swine Diseases
• Animal Disease Emergency Planning
• +۵ مورد دیگر

Dr. Marie Culhane serves as an Associate Professor within the Secure Food Systems Team at the University of Minnesota's College of Veterinary Medicine. With dual expertise as a veterinarian (DVM) and infectious disease researcher (PhD), she focuses on protecting food animal health through advanced epidemiological analysis and emergency response planning. Her educational background includes: BA in English from University of Minnesota, Morris DVM from University of Minnesota, College of Veterinary Medicine PhD in Infectious Diseases from University of Minnesota, College of Veterinary Medicine Dr. Culhane's research centers on influenza A viruses in swine and turkeys, specializing in antigenic and genetic characterization, pathogenesis studies, and vaccination protocol impacts. Her work extends to animal disease emergency planning at local, national, and global levels, with particular emphasis on biosecurity protocols and disease transmission dynamics. Analysis of her recent publications reveals a strong focus on practical applications for the livestock industry, including advanced surveillance systems for African Swine Fever, evaluation of depopulation methods, and optimization of influenza vaccination strategies in commercial production systems. Her research consistently bridges laboratory findings with field applications. Dr. Culhane actively collaborates with USDA APHIS, the Swine Health Information Center, and the Fats & Proteins Research Foundation on numerous funded projects addressing high-consequence food animal diseases. Her media appearances, including commentary on swine flu concerns, demonstrate her role as a trusted expert in veterinary public health. She leads the Secure Food Systems Team, which develops practical solutions for disease prevention and control in food animal production systems, with particular focus on influenza viruses and African Swine Fever. The team works closely with industry stakeholders to implement research findings into real-world biosecurity protocols.

• Architectural Computing
• Building Information Modeling
• Virtual Reality
• +۵ مورد دیگر

Togan Tong serves as Associate Professor in the Department of Building Information at Yıldız Technical University's Faculty of Architecture, where he has maintained continuous academic service since 1992. His expertise spans computational design methodologies and immersive technology applications within architectural practice and education. His educational foundation includes: Bachelor of Architecture from Yıldız University (1988) Master of Architecture in Building Science from Yıldız Technical University (1990) Ph.D. in Building Information from Istanbul Technical University (2000) Research initiatives focus on Architectural Computing , Building Information Modeling , and Immersive Technologies , with particular emphasis on human-computer interaction in design environments. Current projects explore VR/AR interfaces for architectural modeling, computational space planning algorithms, and game-based historical reconstruction systems. Publication analysis reveals a pronounced shift toward immersive educational applications since 2020, with significant contributions in VR ergonomics, spatial cognition studies, and BIM integration methodologies. His work bridges technical computing and architectural pedagogy through systematic reviews and empirical interface studies. Academic mentorship includes supervision of 9 theses across architectural computing disciplines. Professional activities extend to Digital Design Education Consultancy for the Istanbul Metropolitan Branch of the Chamber of Architects, influencing curriculum development at institutional levels. Operational activities center around the YTU Bot Group research collective, utilizing the university's digital design infrastructure for advanced visualization projects and computational prototyping in architectural contexts.

• Computer Science
• Artificial Intelligence
• Virtual Reality
• +۷ مورد دیگر

Ingrid Scholl is a Professor at the University of Applied Sciences Aachen , specializing in computer science education. She teaches modules including Algorithms and Data Structures , Computer Graphics , Image Processing , and Virtual Reality/Augmented Reality . Her interdisciplinary project DataLake - Big Data Analysis and Visualizations focuses on extracting insights from large datasets using VR/AR technologies. Key Research Areas : Artificial Intelligence, Autonomous Systems, Virtual Reality, Medical Imaging, and Parallel Programming. Projects : Development of low-energy sensors for environmental monitoring, digital twin modeling of buildings for VR visualization, and collaborative VR experiences via HTC Vive. Publications highlight her work on autonomous mining vehicles, scene generation for AI training, and volume rendering in VR. Her recent contributions focus on operational design domains and mapping approaches in autonomous systems.

Cécile Duchêneمشاهده پروفایل

مدرس

• GIS
• Cartography
• Spatial Analysis
• +۷ مورد دیگر

Cécile Duchêne is a lecturer and researcher at Gustave Eiffel University , affiliated with the National School of Geographic Sciences (ENSG) and the LaSTIG Laboratory 's MEIG team. With expertise in GIS, cartography, spatial analysis, and multi-agent systems, her work focuses on semantic enhancement of geographic data, qualitative spatial reasoning, and automated cartographic generalization.

Abe Davisمشاهده پروفایل

استادیار

• Computer Graphics
• Computer Vision
• Human-Computer Interaction (HCI)
• +۳ مورد دیگر

Abe Davis is an Assistant Professor of Computer Science at Cornell University in Ithaca, NY, with a research focus at the intersection of Computer Graphics , Computer Vision , and Human-Computer Interaction (HCI) . He leads a research group that develops innovative computational methods for video analysis, augmented reality (AR), and visual editing. Davis previously held postdoctoral positions at Stanford University and Cornell Tech , following his Ph.D. in Electrical Engineering and Computer Science from MIT (2016) and undergraduate degree in Computer Science at Stanford. Education Ph.D. in Electrical Engineering and Computer Science, MIT M.A. in Electrical Engineering and Computer Science, MIT B.S. in Computer Science, Stanford University Davis' research addresses novel problems in computational video editing, AR applications, and structural health monitoring. His group has made significant contributions to visual vibration analysis , light field reconstruction , and video-based sound recovery . Recent work includes Noise-Coded Illumination for fake video detection and MeCapture for mobile AR body change visualization. His publications span top-tier conferences like SIGGRAPH, CVPR, and CHI. Scientific recognition includes being named to Forbes 30 Under 30 (Science, 2015), 5 TED 2015 Technologists , and recognition as one of The 8 most innovative scientists in tech and engineering (2015). His TED 2015 talk on visual vibration analysis gained international attention. The group's work has been featured in Ars Technica , Engadget , and Cornell Chronicle .

Steve Marschnerمشاهده پروفایل

استاد

• Computer Graphics
• Computer Vision
• Realistic Rendering
• +۸ مورد دیگر

Steve Marschner is a Professor of Computer Science at Cornell University and Director of Graduate Studies for the Computer Science department. He is also a part-time Distinguished Graphics Researcher at NVIDIA Research. His research focuses on computer graphics and vision, particularly on how optics and mechanics determine the appearance of materials. Marschner received his Ph.D. in Computer Science from Cornell University in 1998. His thesis was titled "Inverse Rendering for Computer Graphics" and was advised by Donald P. Greenberg, Charles Van Loan, and Leonard Gross. He also holds a Sc.B. in Mathematics-Computer Science from Brown University (1993). His research spans realistic rendering, material models (both optical and mechanical), appearance capture, simulation, and computational photography. Marschner's work addresses fundamental questions about how to make objects appear to be made from specific materials and how to use cameras to measure information needed for creating realistic images. His research has applications in film production, virtual reality, and manufacturing. Marschner's recent publications demonstrate a strong focus on advanced rendering techniques, particularly in differentiable rendering, wave optics, and the appearance modeling of complex materials like hair, fur, and woven fabrics. His work increasingly integrates machine learning approaches with traditional graphics techniques, while maintaining a strong foundation in physical optics and material science. Marschner has received numerous prestigious awards recognizing his contributions to computer graphics: ACM Fellow (2021) SIGGRAPH Academy member (2018) SIGGRAPH Computer Graphics Achievement Award (2015) Sloan Research Fellowship (2006) NSF CAREER Award (2004-2009) Academy of Motion Picture Arts and Sciences Technical Achievement Award (2003) Marschner has advised numerous Ph.D. and Master's students, many of whom have gone on to successful careers in academia and industry. His research has been supported by the National Science Foundation, Autodesk, Google, and Adobe. He has served in leadership roles for major conferences including as Technical Papers Chair for SIGGRAPH Asia 2015 and Papers Committee Member for multiple SIGGRAPH conferences. His work is conducted through the Program of Computer Graphics at Cornell University, where he collaborates with researchers working on various aspects of computer graphics, vision, and appearance modeling. Marschner also maintains a strong industry connection through his part-time role at NVIDIA Research, focusing on real-time graphics applications.

Tobias Güntherمشاهده پروفایل

استاد

• Computer Graphics
• Data Visualization
• Scientific Visualization
• +۳ مورد دیگر

Professor Tobias Günther is affiliated with the Department of Computer Science at Friedrich-Alexander-University Erlangen-Nürnberg (FAU), where he holds the Chair for Visual Computing. His research focuses on advanced visualization techniques, including progressive rendering, flow visualization, and image processing. Email: tobias.guenther@fau.de Office: Room 01.115-128, Cauerstraße 11, 91058 Erlangen Website: Visual Computing Group Günther’s work spans multiple areas within visual computing: Scientific Visualization: Tools for analyzing complex data like jet stream core lines. Computer Graphics: Techniques for stylized rendering (e.g., caustics blending, image triangulation). Data Processing: Methods for geospatial and fluid dynamics data. Notable contributions include: Eurographics 2016 Paper: Stylized Caustics rendering algorithm. EuroVis 2016 Paper: MCFTLE for Lyapunov exponent visualization. GitHub Repositories: Open-source implementations of his research.

Tor Aamodtمشاهده پروفایل

استاد

• Computer Architecture
• GPU Architecture
• Deep Neural Networks
• +۴ مورد دیگر

Tor Aamodt is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia within the Faculty of Applied Science. He has been a faculty member at UBC since 2006 and maintains an active research program in computer architecture with a focus on GPU systems. His academic journey includes a BASc, MASc, and PhD from the University of Toronto, followed by industry experience at NVIDIA where he worked on the memory system architecture of the GeForce 8 Series GPU. Professor Aamodt's research spans computer architecture with particular expertise in accelerators for deep neural networks and graphics processor unit architecture for non-graphics computing. His work has evolved from foundational GPU architecture research to cutting-edge applications in ray tracing, robotics acceleration, and energy-efficient computing. He has made significant contributions to understanding GPU memory systems, interconnect architectures, and the application of GPUs to machine learning workloads. His research group has developed influential tools including the first widely used GPGPU architecture simulator and the Vulkan-Sim ray tracing simulator. His recent publications reveal a strong trend toward real-time ray tracing acceleration and robotics applications, with substantial work on optimizing tree traversal algorithms for ray tracing workloads. The research shows a clear evolution from general GPU architecture studies to specialized hardware-software co-design for specific application domains, particularly in rendering and robotics. His group consistently publishes at top-tier architecture venues including MICRO, ISCA, and ASPLOS. IEEE Micro Top Picks (3 papers) Communications of the ACM Research Highlight MICRO Conference Hall of Fame NVIDIA Academic Partnership Award (2010) NSERC Discovery Accelerator (2016-2019) Google Faculty Research Award (2016) SAMSUNG Global Research Outreach Award (2023) IISWC 2023 Best Paper Award Professor Aamodt has advised numerous graduate students who have gone on to positions at leading technology companies including Google. His research has been supported by major grants from NSERC, NVIDIA, Google, and Samsung. He has served in leadership roles including Program Chair for ISPASS 2013 and General Chair for ISPASS 2014, and was a Visiting Associate Professor at Stanford University during his 2012-2013 sabbatical. His group maintains active collaborations with industry partners and has produced influential open-source tools including GPGPU-Sim and Vulkan-Sim.

Martin Marinovمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Geometric Modeling
• 3D Mesh Processing
• +۳ مورد دیگر

Dr. Martin Marinov is a researcher affiliated with RWTH Aachen University, specializing in computer graphics, geometric modeling, and 3D mesh processing. His work focuses on multiresolution modeling, subdivision surfaces, and GPU-accelerated algorithms for real-time rendering. Research areas: Subdivision surfaces, quad-dominant remeshing, scattered data approximation, and GPU computing. His publications include innovative methods for mesh decimation, feature preservation, and anisotropic remeshing, with applications in computer graphics and geometric modeling. Marinov has contributed to optimizing parameter correction for subdivision surfaces and developing robust algorithms for complex 3D models.

Jianhua Wuمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Mesh Processing
• Surface Reconstruction
• +۳ مورد دیگر

Dr. Jianhua Wu is a researcher affiliated with the Department of Computer Science at RWTH Aachen University , focusing on Computer Graphics and Mesh Processing . His work addresses challenges in 3D modeling, surface reconstruction, and digital watermarking. Department: Department of Computer Science, RWTH Aachen University. Email: wu@informatik.rwth-aachen.de Research Interests: Jianhua Wu’s research centers on Computer Graphics , with a focus on surface splatting , variational approximation , and spectral watermarking of 3D models. His methods improve robustness in geometric data processing and reduce computational complexity for large datasets. Publication Trends: His 2002–2005 work emphasizes mesh decimation , splatting algorithms , and digital watermarking , leveraging techniques like radial basis functions and multiple-choice optimization to enhance efficiency and accuracy. Scientific Awards: Best Student Paper Award, Eurographics Symposium on Point-Based Graphics 2005