Find Academic Supervisors

• Computer Graphics
• Virtual Cinematography
• Automated Camera Control
• +4 more

Christophe Lino is a Faculty Lecturer (PRAG) at Nantes University's Computer Science Department, affiliated with the Image Perception Interaction (IPI) research group. Previously, he held roles including Assistant Professor (ATER) at Nantes and Rennes Universities, postdoctoral researcher at Inria, and R&I Engineer at Télécom Paris/IP Paris. He earned a PhD in Computer Science (2013) and a MS in Visual Computing (2009). His research focuses on virtual cinematography, automated camera control, lighting techniques, and 3D animation. Notable contributions include the Toric Space representation for camera control (SIGGRAPH 2015), real-time cinematography systems, and drone cinematography algorithms. He has been recognized with the 'Best Innovation of the Year' Genie Award (2017) and ANR pioneering grants. Current projects include work on automated video summarization, inverse rendering, and collaboration with Adobe and Technicolor. His ToricCam library, released under GPL, provides tools for implementing camera control algorithms.

Cédric ZanniView profile

Researcher

• Computer Graphics
• Geometric Modeling
• Implicit Surfaces
• +3 more

Cédric Zanni is a post-doctoral researcher affiliated with the IMAGINE team at Laboratoire Jean-Kuntzmann and Inria Rhone-Alpes, University of Grenoble. His work is supported by the ERC Expressive grant under the supervision of Marie-Paule Cani. He focuses on developing the Expressive application and associated C++ library to advance geometric modeling and animation frameworks. Education: Ph.D. in Computer Graphics (specialty: Mathematics-Informatics), University of Grenoble (2013) Master of Science in Applied Mathematics (2010) Graduate of Ecole Nationale Supérieure d'Informatique et Mathématiques de Grenoble (2010) French Preparatory School MPSI/MP (2007) Research Interests: Skeleton-based shape representation (e.g., Scale-Invariant Integral Surfaces: SCALIS) Blending control for implicit surfaces Generating surface details via Gabor noise Applications in 3D manga hair modeling Teaching: 192+ hours across Grenoble engineering schools (2010–2013), focusing on mathematics (analysis), programming (C, Java, C#), and geometric modeling courses. Supervised projects in JPEG decoding and financial structured products assessment.

• 3D Modeling
• Real-time Animation and Simulation
• Virtual Characters
• +9 more

Prof. Damien Rohmer is a Professor of Computer Science at École Polytechnique, part of the Institut Polytechnique de Paris. He leads the VISTA research team at the LIX laboratory (CNRS UMR 7161). His research focuses on 3D modeling, real-time animation, and interactive design, emphasizing efficiency and user control. Key applications include virtual characters, clothing simulation, and natural phenomena modeling for entertainment, medicine, and architecture. Education: PhD in Computer Science from Université de Grenoble (2011), HDR from the same institution (2017), and engineering degrees from CPE Lyon and Université Jean Monnet (2007). Research interests span interactive shape design, real-time physics-based animation, implicit surfaces, and multi-agent systems. Recent awards include the 2025 Eurographics Honorable Mention and multiple awards at MIG/SCA 2024 conferences. He supervises PhD students in animation and modeling projects, funded by ANR and CIFRE grants. Active in academic service, he is Vice Director of LIX and former committee member of AFIG.

Rajmund NagyView profile

Researcher

• Deep Generative Models
• 3D Character Animation
• Motion Synthesis
• +3 more

Rajmund Nagy is a PhD student at the Division of Speech, Music and Hearing at KTH Royal Institute of Technology, supervised by Gustav Eje Henter and Jonas Beskow. His research focuses on deep generative models (e.g., GANs, normalizing flows) and their applications to 3D character animation and motion synthesis. Supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP), his work bridges machine learning and computer graphics to create immersive 3D character experiences. Research Interests: Deep Generative Models 3D Character Animation Motion Synthesis Generative AI for Media Applications Publications highlight advancements in gesture generation and evaluation, including co-organizing GENEA workshops (2021–2024) focused on embodied agents' non-verbal behavior. His contributions span diffusion models for motion synthesis, multimodal analysis of gesture properties, and frameworks for integrating gesture systems into conversational agents. He co-organized workshops at ICMI, ECCV, and SIGGRAPH, and led a study trip to Japanese labs (RIKEN, DeepMind, etc.) for Swedish PhD students.

• Partial Differential Equations
• Computational Fluid Dynamics
• Numerical Analysis
• +3 more

Associate Professor Fabrice Colin is affiliated with the Bharti School of Engineering & Computing at Laurentian University, specifically within the Department of Mathematics and Computer Science. He joined Laurentian University in summer 2005 after a one-year professorship at Université de Moncton, bringing expertise in mathematical modeling and computational methods. His educational background includes a B.Sc., M.Sc., and Ph.D. in Mathematics, with doctoral studies completed in 2002 at Université de Sherbrooke under Professors Tomasz Kaczynski and Michel Willem. Professor Colin's research centers on partial differential equations (PDEs) as foundational tools for modeling phenomena ranging from fluid dynamics to quantum mechanics and biological processes. He maintains an active collaboration with Professor Richard Égli on real-time numerical simulation of fluids (water, smoke, fire), with direct applications in computer graphics, video games, and film production. This work bridges theoretical mathematics and practical computational challenges in visual effects. His publication portfolio demonstrates consistent focus on meshfree methods and fluid dynamics, with recurring themes in stabilization techniques, kernel-based approaches, and nonlinear systems. The research trajectory shows increasing emphasis on real-time computational efficiency for graphics applications while maintaining mathematical rigor in PDE analysis. His scholarly recognition includes: Dean of the Faculty of Science Honor List 2003 (University of Sherbrooke) for doctoral research excellence Dean of the Faculty of Science Honor List 1997 (University of Sherbrooke) for master's research excellence Professor Colin has supervised three master's students through his collaboration with Richard Égli and currently co-supervises two doctoral candidates—one with Professor Kaczynski in mathematical analysis, and another with Professors Benaissa and Megrez in applied computational methods. His research program receives partial funding from the Natural Sciences and Engineering Research Council of Canada (NSERC), supporting both theoretical investigations and practical simulation development. He operates within Laurentian's computational mathematics research environment, contributing to interdisciplinary projects that connect pure mathematics with computer graphics applications through ongoing industry-relevant fluid simulation work.

Carl StrathearnView profile

Lecturer

• Artificial Intelligence
• Robotics
• Human-Robot Interaction
• +5 more

Dr. Carl Strathearn is a Lecturer at the School of Computing Engineering and the Built Environment , Edinburgh Napier University. He works within the Centre for Algorithms, Visualisation and Evolving Systems , focusing on Humanoid Robotics Artificial Intelligence Natural Language Generation Human-Robot Interaction His research includes the CiViL project (2020-2023) funded by the Engineering and Physical Sciences Research Council (£280,060), which explores common-sense and visual-enhanced natural language generation for computational agents. He also contributed to the DanceMark project (2024), developing an open telemetry framework for latency-sensitive VR experiences. Key publication trends show focus areas in Commonsense-Augmented Dialogue Systems Biomimetic Humanoid Design Viseme-Driven Animation Multimodal Turing Testing with applications in museum technology and social robotics. Collaborations include working with Prof. Kenny Mitchell (School of Computing, Edinburgh Napier) Dr. Yanchao Yu (School of Computing, Edinburgh Napier) Prof. Emma Hart (School of Computing, Edinburgh Napier) across multiple projects.

• Computer Graphics
• Visual Effects Education
• Digital Heritage Preservation
• +4 more

Adam Redford is a Senior Lecturer in Computer Animation at Bournemouth University. His research focuses on visual effects (VFX) pipeline education, digital matte painting, photogrammetry applications in bioarchaeology, and cultural heritage preservation using off-the-shelf software. He has contributed extensively to Eurographics education papers and conferences. University: Bournemouth University Department: Computer Animation Redford's work bridges technical innovation with pedagogical strategies in digital media. His recent publications highlight efforts to streamline photogrammetry workflows for bioarchaeological analysis and develop holistic VFX education frameworks. He has also explored creative undergraduate projects in asset integration and digital matte painting. Research Trends: His articles emphasize interdisciplinary approaches, combining computer graphics with cultural heritage and bioarchaeology, alongside educational methodologies for VFX pipelines. Grants: In 2022, he received funding for developing a prototype system for photogrammetric capture and digital fabrication of prosthetic limb sockets. External Roles: Academic Expert for Programme Validation at the Institute of Art, Design, and Technology (2019) External Examiner at the University of the West of Scotland (2017-2020)

Colin GrothView profile

Researcher

• Virtual Reality
• Human Perception
• Computer Graphics
• +3 more

Colin Groth is a postdoctoral researcher at the Max Planck Institute for Informatics , Germany, working with Karol Myszkowski. His research focuses on perception-based techniques in virtual reality (VR), including user experience optimization, cybersickness reduction, and facial emotion manipulation. He earned his Ph.D. (2024) and Master’s (2020) from Technische Universität Braunschweig , Germany, and a research visit at Università della Svizzera italiana , Switzerland. 2024–Present: Postdoc, Max Planck Institute for Informatics 2023: Research Visit, Università della Svizzera italiana 2020–2024: Ph.D., TU Braunschweig 2018–2020: Master’s, TU Braunschweig Colin’s research bridges computer graphics , human perception , and VR technology , with a focus on enhancing user experience through physiological and cognitive insights. He investigates eye tracking , vestibular stimulation , and facial reenactment in immersive environments. His publications reveal trends in virtual reality and perception engineering , including cybersickness mitigation , 360° video compression , and emotion-altering video techniques . Techniques span gaze-contingent image deformation , wavelet-based coding , and electrical muscle stimulation for interaction. Scientific Awards : 2020: KI-Talent Prize, Niedersächsisches Ministerium für Wirtschaft 2022: Honorable Mention for Best Journal Track Paper, IEEE VR He collaborates with researchers like Marcus Magnor, Susana Castillo, and Piotr Didyk. His work is funded by the German Science Foundation (DFG MA2555/15-1) and the Cluster of Excellence PhoenixD.

Sascha HollView profile

Researcher

• Markov Chain Monte Carlo
• Stochastic Partial Differential Equations
• Rendering
• +6 more

Sascha Holl is a researcher at the Max Planck Institute for Informatics , affiliated with the Department 4: Computer Graphics and the Sampling and Rendering Group . Their work focuses on advanced computational methods at the intersection of mathematics and computer graphics. Research Interests Diffusion-based and nonreversible Markov Chain Monte Carlo (MCMC) Stochastic Partial Differential Equations (SPDEs), including stochastic Navier-Stokes equations with multiplicative noise Physically-based and real-time rendering techniques Real-time global illumination for gaming applications Stochastic fluid dynamics and animation Constrained/multi-target/unbounded optimization Functional/stochastic analysis Low-level and graphics programming, including gaming console graphics APIs Contact Details Office: Campus E1 4, Room 209, Saarland Informatics Campus, 66123 Saarbrücken, Germany

Karol MyszkowskiView profile

Professor

• Realistic Image Synthesis
• Global Illumination
• High Dynamic Range Imaging
• +7 more

Karol Myszkowski is a Professor in the Department of Computer Graphics at the Max Planck Institute for Informatics in Saarbrücken, Germany. His research spans realistic image synthesis, high dynamic range imaging, and perception issues in computer graphics. He leads a research group that investigates the intersection of human visual perception and computer graphics techniques to develop more realistic rendering solutions. Institution: Max Planck Institute for Informatics Department: Computer Graphics (Department 4) Location: Campus E1 4, Room 229, Saarbrücken, Germany His research interests focus on realistic image synthesis and global illumination, high dynamic range imaging techniques, stereo 3D visualization, eye tracking applications, computational displays, appearance fabrication, and perception issues in computer graphics. He investigates how human visual perception interacts with rendering techniques to create more efficient and realistic graphics solutions for virtual and augmented reality applications. Recent publications (2023-2025) show a strong trend toward neural rendering techniques, particularly for high dynamic range content processing and generation. His work increasingly integrates deep learning approaches with traditional computer graphics methods, focusing on perception-guided solutions that optimize visual quality according to human visual system characteristics. Key areas include HDR image/video processing, neural radiance fields, image/video deblurring, and multisensory perception studies. Current PhD Students: Martin Bálint, Daniel Jiménez Navarro Former PhD Students: 17 including Mojtaba Bemana, Chao Wang, and Krzysztof Wolski Current Postdoc: Colin Groth Former Postdocs: 11 including Gurprit Singh and Bin Chen His research group collaborates extensively within the Max Planck Institute for Informatics and with other international institutions. The team focuses on bridging the gap between computer graphics techniques and human visual perception, developing novel methods for realistic image synthesis, high dynamic range imaging, and perception-aware rendering solutions for virtual and augmented reality applications.

Lan XuView profile

Assistant Professor

• Computer Vision
• Computer Graphics
• Performance Capture
• +5 more

Lan Xu is a Tenure-track Assistant Professor at the School of Information Science and Technology (SIST) in ShanghaiTech University. His research focuses on computer vision and computer graphics, specifically on capturing, perceiving, and understanding human-centric dynamic and static scenes in complex real-world environments. Dr. Xu received his Ph.D. from the Hong Kong University of Science and Technology (HKUST) in 2020 under Prof. Lu Fang, and his B.E. from Zhejiang University (ZJU) in 2015. Prior to ShanghaiTech, he worked with Prof. Yebin Liu at Tsinghua University (2016) and visited the GVV group at MPI hosted by Prof. Christian Theobalt (2018). His research spans performance capture, 3D/4D reconstruction, scene understanding, and artificial reality , aiming to digitalize humans, objects, and events for realistic tele-presence in VR/AR. His work targets the intersection of computer vision, computer graphics, and machine learning with significant practical applications. Dr. Xu has published extensively in top venues including SIGGRAPH (with two 2024 Best Paper Honorable Mentions), CVPR, TPAMI, and IJCV. In 2024 alone, he had 3 papers at SIGGRAPH Asia, 1 at TPAMI, 3 at ACMMM, 7 at SIGGRAPH, 1 at IJCV, and 9 at CVPR. Best Paper Honorable Mention at SIGGRAPH 2024 (CLAY) Best Paper Honorable Mention at SIGGRAPH 2024 (DressCode) His research group develops cutting-edge technologies for human performance capture and 3D scene understanding, with projects like UnstructuredFusion for real-time 4D reconstruction, EventCap for high-speed motion capture, and FlyFusion for volumetric capture using flying cameras. They focus on practical applications in virtual reality, augmented reality, telepresence, and digital content creation.

Youngjoong KwonView profile

Assistant Professor

• Computer Vision
• Computer Graphics
• Human Performance Capture
• +3 more

Youngjoong Kwon is an incoming Assistant Professor in the Department of Computer Science at Emory University (Fall 2025), with postdoctoral research experience at Stanford University's Translational AI Lab and Vision and Learning Lab, and Carnegie Mellon University's Robotics Institute. He holds a PhD in Computer Science from the University of North Carolina at Chapel Hill and a BS from Yonsei University, Korea. Education: PhD, Computer Science, University of North Carolina at Chapel Hill (2023) BS, Computer Science, Yonsei University (2017) Research: His work bridges Computer Vision and Computer Graphics, focusing on human performance capture, avatar modeling, neural rendering, and telepresence systems. Recent publications demonstrate expertise in sparse view synthesis, deformable light fields, and real-time 3D avatar generation. Awards: Bronze Prize, 27th HumanTech Paper Award, Samsung Electronics Co., Ltd. (2022) Academic Engagement: Active as Area Chair (3DV 2026) and reviewer for top conferences (CVPR, ECCV, NeurIPS, etc.) and journals. Collaborations: Hosted by institutions including University of British Columbia, Max Planck Institute for Intelligent Systems, Stanford University, Adobe Research, NVIDIA Research, Texas A&M University, and Brown University for invited talks.

Congyi ZhangView profile

Research Fellow

• Computer Science
• Neural Shape Representation
• 3D Reconstruction
• +3 more

Congyi Zhang is a postdoctoral research and teaching fellow in the Department of Computer Science at the University of British Columbia. He earned his Ph.D. in Computer Science from Peking University and a B.Sc. in Mathematics from Fudan University. Prior to his current role, he served as a research associate at the Department of Computer Science, Hong Kong University, and as a visiting researcher at the Max Planck Institute for Informatics. His research focuses on neural shape representation, AI-driven 3D content generation, human-computer interaction, and 3D reconstruction techniques. He has contributed to methods that improve geometric accuracy, optimize sampling strategies, and enable efficient local editing of 3D models. Recent publications highlight advancements in neural implicit fields, multiview diffusion models, and efficient 3D mesh creation from 2D inputs. His work balances theoretical innovation with practical applications in digital media, orthodontics, and archaeology. He is currently transitioning to an Assistant Professor position at the Computer Science Department, University of Texas at Dallas, where he seeks motivated Ph.D. students for Spring/Fall 2026 cohorts.

Bastian WandtView profile

Researcher

• Human Motion Capture
• 3D Reconstruction
• Machine Learning
• +3 more

Bastian Wandt is a Researcher at the University of British Columbia in the group of Helge Rhodin, and will join Linköping University as an Assistant Professor in September 2022. He holds a PhD from Leibniz University Hannover (2015–2020) and a Mechatronics degree (B.Sc. 2012, M.Sc. 2015) from the same institution. His research focuses on human motion capture, 3D reconstruction, and machine learning, particularly deep learning techniques for weakly supervised training and probabilistic modeling. He founded the AI consulting company HEUWA in 2018 and has taught courses such as DATA 311 at UBC. Research interests include applying neural networks and dimensionality reduction to human pose estimation, with special emphasis on monocular video analysis and physics-based models. Key contributions involve unsupervised learning methods like ElePose and CanonPose , as well as anomaly detection frameworks like Same Same But DifferNet . Awards include the KI Talent Award (2020, €4,000) for his dissertation. He has supervised numerous theses on topics like pose space modeling, recurrent neural networks for motion capture, and texture synthesis. His work bridges computer vision, robotics, and medical imaging applications.

Mario ZellerView profile

Lecturer

• Virtual Reality
• 3D Graphics
• Media Production
• +3 more

FH-Prof. Dipl.-Ing. (FH) Mario Zeller is a Lecturer at the University of Applied Sciences St. Pölten, affiliated with the Department of Media and Digital Technologies and the Institute of Creative Media Technologies. He teaches in programs including Digital Media Technologies (MA), Digital Design (MA), and Media Technology (BA). His career began with studies in Telecommunications and Media at the same institution, followed by an ORF graphics department internship (2003-2004). Since 2004, he has worked as a post-production freelancer and in real-time 3D on-air graphics at ORF. His research focuses on virtual reality, 3D graphics, and interactive media, with notable projects like the VRinMotion series and Virtual Studio Production initiatives. Key projects include the VRinMotion trilogy exploring immersive motion-based experiences and the 2010 study on virtual studio training systems. He actively contributes to media education through teaching and projects like 'Meta VFX' and 'Unreal Engine Applications.' His work bridges academic research and industry applications in digital media and interactive technologies.