جست‌وجوی استاد و پژوهشگر

Jacco Bikkerمشاهده پروفایل

مدرس ارشد

• Computer Graphics
• Rendering
• Ray Tracing
• +۴ مورد دیگر

Jacco Bikker is a Senior Lecturer at the Academy for AI, Games & Media at Breda University of Applied Sciences, where he founded the CMGT program (formerly known as IGAD) in 2006 together with Frank Peters. With a background in the Dutch game industry as a rendering specialist, he brings practical industry experience to his academic role. Dr. Bikker defended his doctoral thesis on Ray Tracing in Real-time Games in 2012 at Delft Technical University under the supervision of Professor Erik Jansen. His research focuses on cutting-edge graphics techniques including real-time ray tracing on CPU and GPU, path tracing for real-time global illumination, denoising, and artificial intelligence applications for rendering challenges. His work bridges the gap between academic research and industry implementation, with strong emphasis on knowledge transfer to students and practitioners. His research output shows a clear progression from foundational rendering techniques to advanced real-time ray tracing implementations. Early work focused on path guiding and BRDF matching algorithms, while more recent contributions center on practical implementations of real-time ray tracing systems. His research spans both theoretical computer graphics and practical software optimization challenges faced in game development. As an active member of the graphics community, Bikker serves in leadership roles including as Paper Chair for High Performance Graphics (HPG) '24 and as Chair for ACM/Eurographics committees. He regularly presents at industry events and has contributed to press discussions about game development education and technology. Dr. Bikker is the creator of the TinyBVH open-source library, a single-header dependency-free BVH construction and traversal library that has gained significant traction in the graphics community. The library is used by projects including EA SEED's Gigi and Unity implementations, demonstrating its practical impact on real-world graphics applications.

• Computer Graphics
• Rendering
• Color Science
• +۴ مورد دیگر

Privatdozent (Senior Lecturer) Alexander Wilkie is affiliated with the Faculty of Informatics at the Technische Universität Wien , specifically the Institute of Computer Graphics and Algorithms. His research focuses on photorealistic rendering, color science, and optical phenomena. Photorealistic Image Synthesis Bidirectional Reflectance Distribution Function (BRDF) Chromatic Adaptation Spectral Rendering Fluorescence Modeling His work explores layered materials, atmospheric effects, and gemstone simulations, with significant contributions to physically based rendering algorithms. Students under his supervision include Andreas Weidlich and Harald Grasberger. Wilkie has collaborated on projects funded by the Austrian Science Fund (FWF) from 2005–2007.

• Remote Sensing
• Imaging Spectroscopy
• Hyperspectral Sensing
• +۹ مورد دیگر

Jan van Aardt is a Professor and Director of the Chester F. Carlson Center for Imaging Science at the Rochester Institute of Technology (RIT), within the College of Science. His research focuses on remote sensing, imaging spectroscopy, lidar, and unmanned aerial systems (UAS) for environmental and agricultural applications. BSc, Forestry, University of Stellenbosch, South Africa Hons., Forestry (Remote Sensing & GIS), University of Stellenbosch, South Africa MS, Forestry, Virginia Polytechnic Institute and State University PhD, Forestry, Virginia Polytechnic Institute and State University Dr. van Aardt's research centers on the application of hyperspectral, lidar, and multi-temporal remote sensing in forestry and ecosystem monitoring. His work includes forest structural assessment, vegetation physiology, foliar chemistry estimation, and precision agriculture. He actively uses UAS-based sensing for crop yield prediction, nutrient status assessment, and growth stage classification, particularly in snap beans and table beets. His recent publications demonstrate a strong trend in applying UAS-based hyperspectral and lidar data for precision agriculture, with a focus on crop yield modeling, leaf area index estimation, and structural characterization of crops. The integration of multispectral and LiDAR data for biomass and vegetation structure analysis is a recurring theme, especially in forestry and savanna ecosystems. Scientific honors include membership in multiple Technical Working Groups for the National Ecological Observatory Network (NEON) from 2017 to 2021, focusing on airborne sampling design and lidar applications. Dr. van Aardt advises numerous graduate and undergraduate students, and has secured research funding for projects involving geospatial disaster response, forest carbon modeling, and crop health monitoring. He teaches courses in environmental applications of remote sensing, imaging science senior projects, and graduate research. He leads research efforts involving advanced imaging systems and has co-designed drone imaging systems for assessing grape farm health. His lab works with terrestrial and airborne lidar, hyperspectral sensors, and simulation models for scaling photosynthesis and vegetation structure.

Xudong Xuمشاهده پروفایل

پژوهشگر

• Embodied AI
• 3D Scene Generation
• Generative Modeling
• +۳ مورد دیگر

Xudong Xu is a researcher at Shanghai Artificial Intelligence Laboratory, specializing in Embodied AI with a focus on interactive scene generation and 3D object synthesis. He earned his Ph.D. in Information Engineering from The Chinese University of Hong Kong (2018-2023), advised by Prof. Dahua Lin, and holds a Bachelor's degree in Automation from Nanjing University (2014-2018), where he ranked first in his cohort. His research explores compositional scene generation, procedural modeling of articulated objects, and material-aware 3D synthesis. He has published in top venues like SIGGRAPH Asia, ECCV, NeurIPS, and contributed to projects such as MATLABER and RoomTex. His work leverages Gaussian splatting, PBR materials, and occupancy fields for high-fidelity 3D environments. Xudong has received prestigious awards including the Shanghai Leading Talent Program, CUHK Postgraduate Scholarship, and National Scholarship at Nanjing University. He serves as a reviewer for major AI/ML conferences like CVPR, ICCV, and NeurIPS, and mentors interns from institutions such as University of Virginia and UC San Diego.

Xavier Pueyoمشاهده پروفایل

استاد

• Computer Graphics
• Visibility Algorithms
• Realistic Rendering
• +۴ مورد دیگر

Xavier Pueyo is a Professor at the Universitat de Girona (UdG) in the Department of Computer Science, Applied Mathematics and Statistics. He has held academic positions since 1980, including Associate Professor at Universitat Politècnica de Catalunya (1988-1993). His research focuses on Computer Graphics , particularly Visibility Algorithms , Realistic Rendering , Lighting Simulation , and Cultural Heritage applications. Enginyer Industrial (Universitat Politècnica de Catalunya, 1980) Docteur Ingénieur in Informatique (Université de Rennes I, 1984) Doctor Enginyer Industrial (Universitat Politècnica de Catalunya, 1986) His work includes advanced Radiosity algorithms , Monte Carlo methods for Global Illumination, and Weathering simulations for urban environments. He has supervised 11 PhD students and co-authored 15+ significant publications, emphasizing interactive rendering and parallel computing applications. Scientific awards : Fellow of the EUROGRAPHICS Association (2004) Active in grants : Design and Implementation of a Lighting Simulation System (1993-1995) Interactive graphic system for rendering complex images using supercomputers (1993-1994) Computer Graphics Network (1993-1997) Realistic Lighting Simulation (1996-1998) Virtual Reality for Cooperative Design (1999-2001) Lighting Simulation (2005-2007) Energy Efficient Lighting (2008-2010) Advanced Modeling (2014) 3D Geometric Models (2015-2017) Life Sciences Visualization (2018-2021) Digital Heritage Models (2020-2023) He leads the ViRVIG research group and collaborates with institutions across Europe, focusing on Geometry and Graphics Group (GGG) projects.

Michael Shepardمشاهده پروفایل

استاد

• Remote Sensing
• Planetary Photometry
• Asteroid Studies
• +۲ مورد دیگر

Michael Shepard is a Professor of Geosciences at Bloomsburg University , specializing in remote sensing , planetary photometry , and asteroid studies . He teaches courses like Applied Geophysics (EGGS 480) , The Planets (EGGS 106) , and Quantitative Methods (EGGS 150) , emphasizing hands-on geophysical instrumentation training. Department: Physical and Environmental Sciences Research Lab: B.U.G. (Bloomfield University Goniometer) Laboratory Key Instruments: 12-channel seismograph, Worden gravimeter, GSS ground-penetrating radar His research focuses on lunar and martian regolith characterization using photometric goniometers. The BUG Lab, funded by NASA's Planetary Geology and Geophysics Program, investigates bidirectional reflectance distribution functions (BRDF) of celestial materials. Notable projects include calibration target development for Mars Exploration Rovers and diviner mission data validation through Apollo soil studies. Recent publications analyze light scattering behavior in planetary surfaces, with applications to asteroid (16) Psyche and Kleopatra photometry . Collaborations span institutions like Cornell University , UCLA , and JPL . The BUG Lab's data contributes to planetary mission calibration and surface property inference .

Todd Zicklerمشاهده پروفایل

استاد

• Computer Vision
• Computer Graphics
• Machine Learning
• +۸ مورد دیگر

Todd Zickler is the William and Ami Kuan Danoff Professor of Electrical Engineering and Computer Science at Harvard University's John A. Paulson School of Engineering and Applied Sciences (SEAS). His research focuses on modeling light-material interactions and developing computational techniques for visual data interpretation, with applications in autonomy, augmented reality, and computational imaging. He leads the Harvard Computer Vision Laboratory and is part of the Graphics, Vision, and Interaction Group. Education: B.Eng. (Honours Electrical Engineering), McGill University, 1996 Ph.D. (Electrical Engineering), Yale University, 2004 Research Interests: Computer Vision, Computer Graphics, Machine Learning Optical and Computational Imaging, Human Perception Applications in Robotics, AR, and Autonomous Systems Key Contributions: Developed novel depth sensors inspired by jumping spiders Advanced shape-from-texture and shading techniques Contributed to neural radiance fields (NeRF) and boundary detection algorithms Awards: NSF Career Award Alfred P. Sloan Research Fellowship Grants & Labs: Director of Harvard Computer Vision Lab Recipient of NSF AI Institute funding ($20M) for physics-driven AI research

Daljit Singh Dhillonمشاهده پروفایل

استادیار

• Computer Graphics
• Bio-physical Modeling and Simulation
• Realistic Appearances
• +۳ مورد دیگر

Dr. Daljit Singh Dhillon is an Assistant Professor in the Visual Computing division at Clemson University's School of Computing. He joined Clemson in January 2019 after a research associate position at Imperial College London (2017–2018) and a Swiss National Science Foundation fellowship at the University of Geneva (2016–2017). His research focuses on modeling material appearances, surface geometries, and bio-physical systems, with applications in computer graphics, fabrication, and interdisciplinary collaborations. Education PhD in Computer Science, University of Bern, Switzerland (2011–2015) M.Sc. (Engg.), Indian Institute of Science, Bengaluru (2007–2010) Bachelor's in Computer Engineering, University of Mumbai (1995–1999) Research Interests His work bridges visual computing and interdisciplinary fields, emphasizing practical measurement and modeling of materials like skin, holographic surfaces, and biological nanostructures. Notable contributions include spectral skin reflectance modeling, diffraction effects in reptile skin, and feather appearance rendering. He also collaborates on NSF-funded projects, such as developing light-scattering models for bird feathers. Grants & Awards NSF-Small Grant ($477K) for feather light-scattering research (2020) SNSF Early Postdoc Mobility Fellowship (2016–2017) Labs & Teams He leads research on material appearance and surface geometry processing at Clemson, with students like Makayla Master (PhD) and Srihith Alwala (research assistant). Collaborations include paleontologists and biologists for projects like feather structural modeling.

Rafal Mantiukمشاهده پروفایل

استاد

• Computer Graphics
• Imaging Science
• Human Vision Perception
• +۶ مورد دیگر

Rafal Mantiuk is a Professor of Graphics and Displays at the Department of Computer Science and Technology, University of Cambridge. He is affiliated with the William Gates Building on JJ Thomson Avenue. His research interests span Graphics, Vision and Imaging Science, and Human-Centred Computing. He leads a research group focused on perceptual modeling for display technologies, HDR content optimization, and neural network applications in graphics. His academic career includes contributions to computational 3D displays, contrast sensitivity functions (e.g., stelaCSF, castleCSF), and novel datasets like HDR4CV and UPIQ. Notable work involves developing perceptually guided metrics for image/video quality assessment, enhancing holographic and near-eye display technologies, and exploring neural rendering techniques for realistic 3D avatars (e.g., FaceCraft4D). Rafal's research emphasizes bridging the gap between human visual perception and computational graphics, with a focus on optimizing display systems for naturalistic visual experiences. His recent efforts address challenges in augmented reality, stereoscopic depth perception, and adaptive rendering strategies informed by spatiotemporal vision limitations. He has also contributed to benchmarking frameworks for evaluating light field interpolation and neural view synthesis methods. Scientific Contributions: Over 30 publications since 2021, including foundational work on contrast sensitivity models and HDR display calibration. Labs/Teams: Leads the Graphics and Vision research group at the University of Cambridge, collaborating on projects like the FovDots dataset and glare reduction techniques in images.

Michael Kudenovمشاهده پروفایل

استاد

• Optical Engineering
• Biomedical Imaging
• Remote Sensing
• +۵ مورد دیگر

Michael Kudenov is a Professor in the Department of Electrical and Computer Engineering at North Carolina State University. His research focuses on developing novel imaging systems, interferometers, detectors, and anisotropic materials for polarization and spectral sensing applications across ultraviolet to thermal infrared wavelengths. Key areas include biomedical imaging, remote sensing, food safety, and atmospheric monitoring. He holds a Ph.D. in Optical Sciences from the University of Arizona (2009) and a B.S. in Electrical Engineering from the University of Alaska Fairbanks (2005). Education: Ph.D. Optical Sciences, University of Arizona (2009) M.S. Optical Sciences, University of Arizona (2007) B.S. Electrical Engineering, University of Alaska Fairbanks (2005) Dr. Kudenov’s research interests center on advancing snapshot imaging systems to maximize spatial, spectral, and polarimetric data capture. Recent work includes hyperspectral imaging for crop phenotyping, AI-driven disease detection in plants, and flexible organic photodetectors for continuous environmental sensing. He has authored 13 journal articles, 15 conference proceedings, and patents in optical systems design. His funded projects include high-throughput phenotyping for peanut leaf spot resistance and collaborations with agricultural stakeholders. Awards include the 2023 SPIE Fellowship, 2021 University Faculty Scholar recognition, and the 2009 UA Graduate Valedictorian honor. He actively mentors students in undergraduate and graduate research, emphasizing interdisciplinary applications of optical engineering. Notable contributions include a bio-inspired spectropolarimetric sensor and Mueller matrix imaging systems for plant health monitoring. His lab develops technologies for field-deployable platforms, advancing precision agriculture and environmental monitoring through innovative optical instrumentation.

Pierre Poulinمشاهده پروفایل

استاد

• Computer Graphics
• Realism
• Image Synthesis
• +۶ مورد دیگر

Pierre Poulin is a Full Professor in the Department of Computer Science and Operations Research at the Université de Montréal. He leads the LIGUM laboratory and has held roles such as Department Chair (2017–2021) and PREDOC responsible (2023). His research focuses on computer graphics, realism, and image synthesis, with expertise in global illumination, procedural modeling, and real-time rendering. Poulin holds a Ph.D. from the University of British Columbia (1993), M.Sc. from the University of Toronto (1989), and B.Sc. from Université Laval (1986). His research spans natural phenomena simulation, fluid dynamics, and interactive visualization. Notable awards include the CHCCS Achievement Award (2021) and Fellow of Eurographics France (2022). He has supervised over 50 students, contributing to advancements in rendering algorithms and software visualization. Key grants include funding from CRSNG and FRQNT for projects on procedural scene creation and fluid simulation. His work bridges academia and industry, with collaborations in animation, visualization, and software engineering.

Donald Greenbergمشاهده پروفایل

استاد

• Computer Graphics
• Real Time Realistic Image Generation
• Color Science
• +۷ مورد دیگر

Donald Greenberg is the Jacob Gould Schurman Professor of Computer Graphics at Cornell University, affiliated with the College of Architecture, Art, and Planning (AAP) and the Department of Architecture. He holds joint teaching responsibilities across Computer Science, Art, and the Business School, reflecting his interdisciplinary impact. His office is located in Rhodes Hall and Sibley Hall at Cornell. Greenberg earned his B.C.E. from Cornell in 1958 and his Ph.D. in 1968, with additional studies at Columbia University. His academic journey has been deeply rooted at Cornell, where he has taught and researched since 1966. His research interests center on computer graphics, with a focus on real-time realistic image generation, color science, and computer-aided architectural design. He pioneered the concept of physically accurate and perceptually indistinguishable digital imagery, laying the foundation for modern rendering and digital twin technologies. His current work includes the development of 'digital twins' for architectural design, enabling real-time simulation of energy use, sunlight, and weather impacts. The selected publications reflect a career-long trajectory from foundational work in computer graphics in architecture to advanced frameworks for realistic image synthesis. These works span disciplines including computer science, architecture, and visualization, emphasizing physically based modeling, interdisciplinary applications, and educational innovation. Scientific Awards: Fellow, American Association for the Advancement of Science (2002) ACSA Creative Research Award in Architecture (1997) Member, National Academy of Engineering (1991) National Computer Graphics Association Academic Award (1989) ACM SIGGRAPH Steven A. Coons Award (1987) Greenberg has advised numerous graduate students, including Rob Cook (Pixar, Oscar winner) and Michael Cohen (Microsoft Research, Facebook), many of whom have achieved significant recognition. He emphasizes student-led research, with nearly 90% of his published papers featuring students as first authors. He leads the multidisciplinary Program of Computer Graphics and collaborates across departments and colleges. His current course, 'Design in the Age of Digital Twins,' exemplifies his ongoing commitment to innovation in education and research. He founded and directs the Program of Computer Graphics at Cornell, a hub for interdisciplinary research involving architecture, computer science, and the arts. The program has nurtured generations of leaders in graphics and visualization, including Kavita Bala, now dean of the Cornell Bowers College of Computing and Information Science.

Gaël Obeinمشاهده پروفایل

دانشیار

• Optical Metrology
• Photometry
• Spectrophotometry
• +۴ مورد دیگر

Gaël Obein is a Senior Lecturer (HDR) and Associate Professor at Conservatoire National des Arts et Métiers (CNAM) in Paris, France. He serves as Director of LNE-CNAM, the national metrology laboratory for radiometry, photometry, temperature, and length, and leads the 'Radiometrics/Photonics' team. His academic career spans roles at CNAM, Paris VI, NIST (USA), and MNHN, with a PhD in 'Physical Systems and Metrology' (2003) and HDR since 2019. President of French Lighting Association (AFE) Secretary of CIE Division 2 Coordinator of four European research projects (2013–2027) Expert in BRDF, BSSRDF, and BTDF metrology His research focuses on optical metrology for material appearance, including: High-angular-resolution goniospectrophotometry (0.015°) µBRDF measurements for 50µm surfaces Specular gloss perception studies Development of primary standards for BRDF/BSSRDF/BTDF Light polarization and speckle effects Scientific Leadership includes: Secretary of CIE Division 2 Director of CIE TC2-85 and JTC17 Coordination of EURAMET-PR-K6 key comparisons Participation in 4 CIE technical committees Publications (2023–2024) cover bidirectional reflectance distribution functions, gloss metrology, spectral irradiance traceability, and material appearance modeling. Projects include 'xDReflect', 'BiRD', 'BxDiff', and 'xDDiff', addressing multidimensional optical diffusion and appearance measurement standards.

Romain Pacanowskiمشاهده پروفایل

پژوهشگر

• Material Appearance Representation
• BRDF Modeling
• Computer Graphics
• +۳ مورد دیگر

Romain Pacanowski is a Research Scientist at INRIA Bordeaux South-West, a French national research institute for computer science and applied mathematics. His work bridges computer graphics, optics, and physics with a focus on material appearance representation and rendering techniques. His primary research interests center on Material Appearance Representation, with specific focus on BRDF modeling and acquisition. He works closely with opticians and physicists to improve the quality and speed of (SV)-BRDF and roughness acquisition. His research also involves developing new mathematical representations and parametrizations of the BRDF space. Additional interests include Global Illumination for both offline and real-time rendering systems, sketched-based UI for highlight design, and emerging technologies like OptiX for hybrid rendering systems. His publication record shows a consistent focus on BRDF modeling, material appearance, and rendering techniques. His recent work (2016-2018) particularly emphasizes diffraction effects in material measurements, novel BRDF representations, and efficient sampling techniques for rendering. He frequently collaborates with researchers from academic institutions while working at the INRIA research institute. Pacanowski maintains an active research program with numerous publications in top computer graphics venues including SIGGRAPH, Eurographics, and Computer Graphics Forum. His work combines theoretical modeling with practical implementation, often providing open-source tools like the ALTA BRDF Analysis Library.

Rafał Mantiukمشاهده پروفایل

استاد

• Visual Perception
• High Dynamic Range (HDR) Imaging
• Display Algorithms
• +۱۰ مورد دیگر

Rafał Mantiuk is a Professor of Graphics and Displays at the Department of Computer Science and Technology , University of Cambridge, UK. He leads the Rainbow Research Group and works on visual perception, display algorithms, and computational imaging. His academic journey includes a PhD (summa cum laude) from Max-Planck-Institut (2006) and an MSc from Technical University of Szczecin (2003). His research spans applied visual perception , high dynamic range imaging , display algorithms , and machine learning for image synthesis . Recent work focuses on ColorVideoVDP (HDR video metrics), AR-DAVID (AR display artifacts), and elaTCSF (flicker modeling). His methodologies combine psychophysics with computational models to enhance display technologies. His awards include: SIGGRAPH Test-of-Time Award (2023) ICME Grand Challenge Second Place (2025) CIC Best Paper Awards (2022, 2020) Human Vision and Electronic Imaging Best Paper (2020) Heinz Billing Award (2006) Key grants: ERC Consolidator Grant (2017) for EyeCode, MSCA RealVision (2018), and EPSRC funding (2017, 2011). He supervises projects involving novel display technologies like HDR multi-focal stereo displays and 10-bit LCD systems.