جست‌وجوی استاد و پژوهشگر

Holly Rushmeierمشاهده پروفایل

استاد

• Computer Graphics
• Data Visualization
• 3D Modeling
• +۴ مورد دیگر

Holly Rushmeier is the John C. Malone Professor of Computer Science at Yale University, with affiliations spanning academic leadership and industry collaboration. Previously, she held roles at Georgia Tech, the National Institute of Standards and Technology (NIST), and IBM Research. She earned BS, MS, and PhD degrees in Mechanical Engineering from Cornell University (1977–1988), followed by engineering roles at Boeing and Washington Natural Gas Company. Her research focuses on computer graphics, 3D modeling, material appearance design, and cultural heritage preservation. Notable projects include digitizing Michelangelo’s Florence Pieta and Egyptian artifacts, and developing tools like Hyper3D for cultural heritage analysis. She has led efforts in visualization software for biology, medicine, and environmental monitoring. Rushmeier has held editorial roles for ACM Transactions on Graphics , IEEE Transactions on Visualization and Computer Graphics , and others. Her recent work emphasizes AI-driven tools for 3D hair simulation, motion capture for dance preservation, and ethical considerations in computer graphics research. Her contributions span academic and applied domains, including collaborations with art conservators and biomedical researchers. She has organized major conferences like SIGGRAPH and IEEE Visualization, shaping the field’s trajectory through leadership and innovation.

Alan H. Barrمشاهده پروفایل

استاد

• Computer Graphics
• Biophysics
• Medical Computing
• +۵ مورد دیگر

Alan H. Barr is a Professor of Computer Science at the California Institute of Technology (Caltech), within the Division of Engineering and Applied Science. He holds a B.S., M.S., and Ph.D. from Rensselaer Polytechnic Institute (1973-1983). His career includes roles as Research Fellow (Caltech, 1984), Assistant Professor (1984-90), Associate Professor (1990-98), and Professor (1998–present). He served as Executive Officer for Computer Science from 2000-2001. Education : B.S., Rensselaer Polytechnic Institute, 1973 M.S., Rensselaer Polytechnic Institute, 1976 Ph.D., Rensselaer Polytechnic Institute, 1983 His research focuses on the mathematical foundations of computer graphics, biophysical modeling, and space mission design. Key interests include predictive simulation methods, computational biophysics, GPU computing, and collaborations with NASA's JPL on the InterPlanetary Superhighway. He has pioneered methods like elastically deformable models and constrained optimization frameworks. Publications highlight advancements in ray tracing, deformable models, and medical imaging. Notable awards include the ACM SIGGRAPH Achievement Award (1988) and ACM Fellow (1995). Awards : ACM SIGGRAPH Achievement Award (1988) ACM Fellow (1995) Barr has advised numerous students whose work spans Pixar, NVIDIA, and academia. He leads the Caltech Computer Graphics Group, collaborating on projects like the Global Virtual Hospital and Goal-Directed MRI.

• Generative Models
• Machine Reasoning
• AI Safety
• +۳ مورد دیگر

Dr. Chris Willcocks is an Associate Professor in the Department of Computer Science at Durham University, specializing in generative models and machine reasoning. He has authored over 35 peer-reviewed publications in top-tier venues including ICLR, TPAMI, CVPR, and IEEE TIFS. His research group has made significant contributions to theoretical generative modeling, including ∞-Diff for infinite-resolution synthesis and anomaly detection techniques like AnoDDPM. His research interests focus on theoretical generative modeling, machine reasoning frameworks, and AI safety. Key projects include diffusion models in Hilbert spaces, gradient origin networks, and applications in medical anomaly detection and security threat analysis. Teaching responsibilities include deep learning, reinforcement learning, and cybersecurity modules. Industry collaborations span multinational corporations (P&G, Unilever, Dyson) and public sector organizations (NHS, DSTL), with over 15 invited talks on AI ethics and cybersecurity. Awards include fellowship of the Higher Education Academy. Professional activities include serving as area chair for BMVC and admissions tutor for computer science. Willcocks supervises multiple postgraduate students including Jonathan Frawley and Rita Liu, and maintains a YouTube channel with educational content on deep learning.

• Virtual Reality (VR)
• Computer Graphics
• Human-Computer Interaction
• +۳ مورد دیگر

Alejandro Beacco Porres is a Researcher at the Universitat Politècnica de Catalunya (UPC) in the Department of Computer Science, affiliated with the Barcelona School of Informatics (FIB). He is a core member of the ViRVIG research group focusing on Virtual Reality, Real-Time Graphics, and Crowd Simulation. His work bridges computer graphics, human-computer interaction, and clinical applications of VR. Research interests include real-time crowd rendering techniques, embodied VR experiences, and applications in mental health. Notable contributions include QuickVR toolkit development, studies on virtual body ownership effects, and VR-based therapy for anxiety and psychosis. He has collaborated extensively with Prof. Mel Slater and international teams on projects funded by Horizon Europe and Spanish National Research Programs. Publications span high-impact journals like Scientific Reports, IEEE Transactions, and The Lancet Psychiatry. His work explores both technical advancements (e.g., avatar reconstruction from images) and socio-ethical implications of VR. Active in both academia and industry, he has led projects addressing cultural heritage visualization and medical training simulations. Education includes a PhD in Computer Science from UPC (2014), with dissertation on real-time crowd simulation. He maintains strong ties with the European Association for Computer Graphics (Eurographics) through conference organizing and peer review activities.

• Real-time Physics Simulation
• Character Animation
• Computer Science
• +۳ مورد دیگر

Sheldon Andrews is a Professor of Software & IT Engineering at the École de technologie supérieure in Montreal, Canada. His research focuses on real-time physics simulation, character animation, and interactive systems. He specializes in integrating computational methods with visual and haptic feedback, particularly in dynamic environments. Research interests include developing algorithms for realistic simulations, such as friction modeling, texture synthesis, and inverse kinematics. His work bridges computer graphics, robotics, and software engineering, with applications in interactive hand simulation and motion gaming. Notable contributions include papers on fingertip appearance modeling (MIG 2013), Hessian matrix-based kinematics (MIG 2017), and friction-visual coupling (SCA 2021). His open-source projects, such as hessianIK and slrbs , provide tools for academic and industrial use. He maintains an active GitHub repository for research code and collaborates on projects like real-time physics engines and data-driven animation techniques. No academic awards are explicitly listed in the provided texts.

Papaioannou Georgiosمشاهده پروفایل

استادیار

• Real-time Computer Graphics
• Virtual Reality
• Photorealistic Imaging
• +۳ مورد دیگر

Georgios Papaioannou Georgios Papaioannou is an Assistant Professor at the Department of Informatics, Athens University of Economics and Business (AUEB). He holds a BSc and PhD in Informatics/Computer Science from the National and Kapodistrian University of Athens. His research focuses on real-time computer graphics, virtual reality, photorealistic rendering, and 3D pattern recognition with applications in cultural heritage digitization and interactive environments. Education BSc in Informatics, National and Kapodistrian University of Athens PhD in Computer Science, National and Kapodistrian University of Athens Research Interests His work spans real-time rendering techniques, virtual reality systems, 3D object reconstruction, and cultural heritage preservation. Notable projects include the PRESIOUS EU project for predictive digitization of cultural objects and the Virtual Archaeologist system for fractured artifact reassembly. Key Contributions Dr. Papaioannou has authored influential papers on global illumination algorithms, volume-based ambient occlusion, and real-time graphics optimization. His work integrates computer vision and machine learning to solve challenges in interactive visualization and archaeological reconstruction. Professional Activities A member of Eurographics, ACM, and SIGGRAPH, he actively reviews for top computer graphics conferences. His lab focuses on advancing real-time rendering technologies for immersive applications, including VR systems for cultural heritage education and historical reenactment.

Gurprit Singhمشاهده پروفایل

پژوهشگر

• Monte Carlo Integration
• Markov Chain Monte Carlo Sampling
• Generative AI
• +۳ مورد دیگر

Gurprit Singh is a Researcher at the Max Planck Institute for Informatics, Saarbrücken, Germany. His work focuses on advancing Monte Carlo integration techniques and their applications in generative AI, physically based rendering, and optimization. He has contributed to conferences such as SIGGRAPH, Eurographics (EG), and Pacific Graphics (PG), serving in roles like Technical Program Committee member and co-chair for Doctoral Consortium programs. Roles: Associate Senior Researcher, Conference Co-chair (EGSR 2021), and active in academic service. Research Interests: Monte Carlo methods, MCMC sampling, gradient-based optimization, and generative models. His research bridges rendering, optimization, and AI, with notable work on noise optimization in diffusion models and perceptual error minimization. He has received the Best Student Paper Award at ICPRAM 2025.

Aanjaneya Mridulمشاهده پروفایل

دانشیار

• Computer Graphics
• Scientific Computing
• Programming Languages
• +۳ مورد دیگر

Aanjaneya Mridul is an Associate Professor in the Department of Computer Science at Rutgers University, where he joined in 2017. He is also a member of the Computational Biomedicine Imaging and Modeling Center (CBIM). His research spans computer graphics, scientific computing, programming languages, and robotics, with a focus on developing numerical methods in computational physics that leverage modern computing power. Dr. Aanjaneya completed his doctoral studies in Computer Science from Stanford University in 2013 under Ronald Fedkiw, followed by postdoctoral studies at the University of Wisconsin-Madison with Eftychios Sifakis. He received his undergraduate degree in Computer Science and Engineering from the Indian Institute of Technology Kharagpur in 2008. His research interests include: Computer graphics and visual simulation Scientific computing and numerical methods Programming languages for computational physics Robotics and differentiable physics engines Computational physics for interdisciplinary applications Dr. Aanjaneya's recent work has focused on applying numerical methods to robotics for learning unknown physical parameters, and designing correctly-rounded implementations of elementary functions for new floating-point variants. His long-term goal is to enable next-generation algorithms that facilitate interdisciplinary collaboration with researchers in engineering and medicine. He has received several prestigious awards including the Ralph E. Powe Junior Faculty Enhancement Award (2019) and the NSF CAREER Award (2023). Ralph E. Powe Junior Faculty Enhancement Award (2019), sponsored by Oak Ridge Associated Universities (ORAU) NSF CAREER Award (2023) At Rutgers, Dr. Aanjaneya directs the Laboratory for Interactive Virtual Environments (LIVE), where he mentors PhD students and postdoctoral researchers. He has secured multiple NSF grants including the CAREER award, an NSF NRI grant with Professors Boularias and Yu, and grants with Professor Santosh Nagarakatte for projects on formally certified low-dimensional linear programs and correctly rounded math libraries. Outside of his academic work, Dr. Aanjaneya enjoys running, rock climbing, hiking, watching movies, and playing piano.

Bernd Bickelمشاهده پروفایل

استاد

• Computational Design
• Digital Fabrication
• Computer Graphics
• +۷ مورد دیگر

Bernd Bickel is a Full Professor for Computational Design at ETH Zurich, embedded in the Design++ research center. He holds a Master's degree from ETH Zurich and a PhD from ETH Zurich under Markus Gross. Previously, he was at IST Austria (2015–2023), Disney Research, and TU Berlin as a visiting professor. His research focuses on computational design, digital fabrication, and simulation, with applications in robotics, computer vision, and material science. Key interests include physics-based simulation, geometry processing, and interdisciplinary engineering. Notable awards include the Academy of Motion Picture Technical Achievement Award (2019), SIGGRAPH's Significant New Researcher Award (2017), and the EUROGRAPHICS Best PhD Thesis (2012). He leads the Computational Design Lab at ETH Zurich and collaborates with institutions like Inria Nancy on projects such as MFX team collaborations. His work spans academic contributions (over 50 publications) and industrial applications, including the FlexMaps Pavilion (First Prize at IASS 2019) and computational tools for 3D printing. He actively mentors PhD students and oversees grants like ERC Starting Grant 'Materializable'.

Zahra Montazeriمشاهده پروفایل

مدرس

• Computer Graphics
• Physics-based Rendering
• Material Modeling
• +۳ مورد دیگر

Zahra Montazeri is a Lecturer (Assistant Professor) in the Department of Computer Science at the University of Manchester. Her research focuses on physics-based computer graphics, particularly photorealistic rendering and appearance modeling for complex materials like cloth, hair, and fur. She holds a PhD in Computer Science from the University of California, Irvine (UCI), and has industry experience at Disney Research, WetaDigital, Industrial Light & Magic (ILM), Pixar, and Luxion. **Education:** PhD in Computer Science (UCI, 2015–2021) M.Sc. in Computer Science (UCI, 2015–2017) B.Sc. in Computer Engineering (Sharif University of Technology, Iran, 2010–2014) **Research Interests:** Zahra’s work bridges academic and industrial applications, emphasizing practical and efficient rendering techniques. Her key areas include physics-based rendering, material modeling for fabrics, and virtual reality optimizations like foveated rendering. She collaborates with industry leaders such as WetaDigital and has contributed to movies like The Mandalorian and Avatar: The Way of Water . **Articles Trends:** Recent work focuses on texture-free cloth rendering, dynamic BTF synthesis, and neural-based material models. Her research often addresses computational efficiency while maintaining photorealism, with applications in film, gaming, and VR. **Awards:** Best Paper Award at EGSR (2023) Best Visuals Award at EGSR (2023) UCI Doctral Fellowship (2015) LightSpeed Venture Partners Summer Fellowship (2016) **Advising & Grants:** Advises four PhD students and has one alumni (David Petrescu). Her group actively collaborates with industry and explores applied research in rendering and virtual environments. She serves on program committees for PG, EGSR, and I3D. **Labs/Teams:** Leads a research group at Manchester focused on graphics and virtual environments, with interdisciplinary projects in computer vision, AI, and material science.

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.

Simeng Qiuمشاهده پروفایل

مدرس

• Computational Imaging
• Computer Vision
• Computer Graphics
• +۴ مورد دیگر

Dr. Simeng Qiu is a Lecturer in Visual Computing at Swansea University's Department of Computer Science (Faculty of Science and Engineering). She leads research in computational imaging, integrating methods from computer vision, computer graphics, optics, and deep learning. Her work focuses on hardware-software co-design to solve imaging challenges. Education: PhD completed in December 2023 under Prof. Wolfgang Heidrich’s group. Research interests include inverse problems, biomedical imaging, and optical sensor design. Recent initiatives include founding Women in Mathematics and Computer Science (WiMACS) at Swansea and securing UK-France Springboard Program funding. She actively supervises postgraduate students and teaches the CS-165 module (Introduction to Data Science). Notable collaborations include work with Université Grenoble Alpes and KAUST. Awards include a Higher Education Research Capital (HERC) grant and recognition at international conferences (e.g., SIGGRAPH, ICCP).

Hadrien Courtecuisseمشاهده پروفایل

پژوهشگر

• Medical Robotics
• Real-Time Simulations
• Finite Element Methods
• +۳ مورد دیگر

Dr. Hadrien Courtecuisse is a Researcher (Chargé de Recherche) at CNRS, affiliated with the AVR/ICube team in Strasbourg since 2013. He holds a Ph.D. in Computer Science from Inria (2011), specializing in parallel architectures for medical simulations. His postdoctoral work at Cardiff University (2012) focused on biomechanical modeling of soft tissues. He later contributed to the Institut Hospitalo-Universitaire (IHU) as a research engineer. His expertise spans sparse linear algebra, real-time simulations, GPU computing, and medical robotics, particularly in surgical training systems and robotic control using inverse finite element models. Education: Ph.D., SHAMAN Team, Inria (2011) Postdoctoral Research, IMAM, Cardiff University (2012) Research Interests: Courtecuisse’s work emphasizes real-time computational methods for medical applications, including deformable object simulation, haptic feedback, and robotic assistance. He develops algorithms for contact response, topological changes, and parallel computing to enhance surgical training and robotic precision. His contributions address challenges in needle insertion, soft tissue interaction, and real-time error control in surgical simulations. Awards & Recognition: No specific scientific awards mentioned. Key Projects: MIMESIS Project (Inria): Focuses on medical robotics and real-time simulation for therapy planning. SOFA-FrameWork: Contributed to open-source simulation software for deformable objects and haptics. Calipso: Image editing via physics-based CAD models. Labs & Teams: Active in the AVR/ICube team at CNRS, collaborating with Inria and international institutions like Cardiff University.

Sara Fridovich-Keilمشاهده پروفایل

استادیار

• Computational Imaging
• Machine Learning Foundations
• Signal Processing
• +۳ مورد دیگر

Sara Fridovich-Keil is an Assistant Professor in the School of Electrical and Computer Engineering at Georgia Tech, where she is also program faculty in machine learning. Previously, she was a postdoctoral researcher at Stanford University (2023–2025), advised by Gordon Wetzstein and Mert Pilanci, and completed her Ph.D. in Electrical Engineering and Computer Sciences at UC Berkeley in 2023 under the guidance of Ben Recht. Her research focuses on the foundations of machine learning, signal processing, and optimization, with applications to computational imaging, medical imaging (e.g., MRI, CT, cryo-EM), and inverse problems. Her work bridges theory and practice, addressing challenges such as nonlinear tomographic reconstruction, data-driven prior design, and signal representation for inverse problems. Key contributions include Plenoxels (radiance field reconstruction without neural networks) and K-Planes (space-time appearance modeling). She is supported by an NSF Mathematical Sciences Postdoctoral Research Fellowship and has received the UC Berkeley Demetri Angelakos Memorial Achievement Award (2022). Her lab at Georgia Tech seeks to develop scalable, provably accurate algorithms for imaging applications. She advises students interested in machine learning, optimization, and signal processing. Professional activities include membership on the IEEE Signal Processing Society’s Computational Imaging Technical Committee (2025–2027). Personal interests include hiking, gardening, and open-source contributions (e.g., GitHub repositories like Plenoxels and FingertipVideo for vital sign estimation).

Enrico Tassiمشاهده پروفایل

پژوهشگر

• Interactive Theorem Proving
• Formal Verification
• Type Theory
• +۵ مورد دیگر

Enrico Tassi is a researcher at Inria, France, affiliated with the STAMP team. His work focuses on the technology of formal proofs, particularly type theory, interactive theorem proving, and its application to formalizing mathematics. He is a key contributor to the development of tools like Coq-Elpi , Hierarchy-Builder , and the small scale reflection Coq extension. His research spans proof assistant architecture, software design, and formal verification, with a strong emphasis on free software principles. Enrico completed his Ph.D. at the University of Bologna in 2008, where he designed the Matita interactive theorem prover. He contributed to the formalization of the Odd Order Theorem and the Paral-ITP project, aiming to scale Coq for large mathematical libraries. His software projects include Elpi , a meta-language for proof assistants, and past contributions to Debian as a developer (2006–2016), focusing on integrating the Lua language into Debian systems. His publications highlight innovations in unification algorithms, tactical design, and proof structuring techniques. Articles address challenges in bi-directional type inference, pattern-based proof command focusing, and nonuniform coercion implementations. His work on small-scale reflection and Hierarchy-Builder demonstrates expertise in algebraic hierarchies and formal library management. Current efforts target enhancing OCaml-based systems through Elpi's high-level programming capabilities. Key Collaborations : Mathematical Components team (INRIA), D.A.M.A. Project Major Tools : Coq-Elpi, Hierarchy-Builder, Matita Formalization Efforts : Ordered Uniformities, Odd Order Theorem, Finite Group Theory