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Anders LoggView profile

Professor

• Digital Twin Cities
• Finite Element Methods
• Computational Fluid Dynamics (CFD)
• +5 more

Anders Logg is a Professor of Computational Mathematics at Chalmers University of Technology , Sweden. He serves as Director of the Digital Twin Cities Centre and leads the interdisciplinary VirtualCity@Chalmers project, aiming to build digital twins of urban environments for simulating traffic, wind flow, pollution dispersion, and flooding. Expertise in finite element methods and FEniCS software development Pioneer in mesh generation with tools like mshr Active in scientific computing and domain-specific languages His research team includes experts in mathematical modeling, Unreal Engine development, and building information modeling . Recent work focuses on integrating IoT with digital twins for energy management and developing scalable simulation frameworks for urban planning. Key research trends across publications include: Digital twin technologies for urban environments Mesh generation in complex geometries Multiphysics simulations (fluid dynamics, heat transfer) Automated computing through domain-specific languages Machine learning integration with urban modeling

• Urban Planning
• Visualization Techniques
• 3D City Modeling
• +3 more

Beata Stahre Wästberg is an Associate Professor and senior researcher at Chalmers University of Technology in the Interaction Design and Software Engineering department. Her interdisciplinary research focuses on visualization in urban planning , particularly addressing how 3D city models can effectively communicate invisible environmental factors like air quality, noise, and social impacts. Research Evolution: Transitioned from perceptually realistic color and light simulation in virtual environments to environmental data visualization in urban contexts Collaborations: Works with researchers across disciplines and stakeholders from municipalities, government agencies, and businesses Key Projects: Leads initiatives like MiljöVIS , SolVis , and SCENDA funded by organizations including Formas and Energimyndigheten Her visualization work emphasizes cross-disciplinary communication and public dialogue , developing tools that integrate environmental data , cultural values , and infrastructure planning into digital twins and VR urban models . While no specific awards are listed, her research has secured consistent funding for environmental visualization projects.

• Robotics
• Human-Computer Interaction
• Haptics
• +3 more

Nizar Ouarti is an Associate Professor at ISIR (Institute of Intelligent Systems and Robotics), Sorbonne University, and a member of the ASIMOV research team. His work focuses on robotics, haptics, and human-computer interaction. His research spans haptic communication of emotions using air jet stimulation, operator-controlled nanomanipulation with virtual reality, and gaze tracking systems enhanced by visual attention models. He also applies signal processing techniques, including non-stationary wavelet packets, to denoising problems. His work bridges human perception and machine interfaces for applications in medical and industrial robotics. His publications demonstrate a strong trend in multimodal human-robot interaction, with emphasis on tactile and visual feedback. Key areas include nanomanipulation, emotion recognition through haptics, and real-time gaze tracking, showing interdisciplinary integration of robotics, signal processing, and cognitive science. Ouarti is an active member of the ASIMOV team at ISIR, which develops intelligent robotic systems for precise manipulation and human-centered applications.

Romain VergneView profile

Associate Professor

• Computer Graphics
• Visual Perception
• Shape Depiction
• +5 more

Romain Vergne is an Associate Professor at the University of Grenoble Alpes, France, and a researcher affiliated with the Maverick team (Inria, LJK) since 2012. Previously, he conducted postdoctoral research at Justus Liebig University Giessen (Germany). His research focuses on the phenomenological links between shapes, light, and material perception, aiming to develop perceptually plausible computer graphics tools. Key interests include shape depiction, visual perception, texture synthesis, and appearance control via his GPU-centric node-based system Gratin for 2D/3D data manipulation. Best Paper Awards: AFIG 2018, Expressive 2018, AFIG 2015 Honorable Mentions: NPAR 2011, I3D 2010 Recent publications explore Gabor noise optimization, motion-coherent stylization, and non-photorealistic rendering frameworks. He also contributes to eco-feedback visualization systems and cartographic style extensions.

Pierre BénardView profile

Associate Professor

• Computer Graphics
• Image Synthesis
• 3D Modeling
• +3 more

Pierre Bénard serves as an Associate Professor at the University of Bordeaux, conducting research with the manao team at LaBRI (CNRS, Inria). His academic career spans teaching and research in computer graphics with notable industry experience at Pixar Research Group and academic work at the University of Toronto. Dr. Bénard earned his PhD from the MSTII Doctoral School of Université de Grenoble in July 2011 under the supervision of Joëlle Thollot and François Sillion at Laboratoire Jean Kuntzmann. His educational background forms the foundation for his expertise in graphics systems and visualization techniques. His research focuses on computer graphics with specializations in image synthesis, 3D modeling, and animation techniques. His work bridges theoretical computer graphics with practical implementation, particularly evident in his teaching of OpenGL-based rendering systems and shader programming. His research interests encompass visual effects creation, non-linear animation techniques, and real-time graphics programming for multimedia applications. As an educator, Dr. Bénard teaches advanced courses including Advanced Image Synthesis (M2), 3D Worlds (M1), and C++ Programming for Multimedia. His teaching philosophy emphasizes hands-on implementation of graphics concepts using modern OpenGL frameworks and C++ programming techniques. His course materials demonstrate a commitment to teaching object-oriented programming principles through practical graphics applications. Dr. Bénard leads research activities within the manao team at LaBRI, focusing on innovative graphics techniques and visual effects. His industry experience at Pixar complements his academic work, providing practical insights into production-level graphics systems. His research environment fosters collaboration between academic theory and industry application in the computer graphics domain.

Thomas EngelhardtView profile

Researcher

• Real-Time Rendering
• Global Illumination
• 3D Graphics
• +4 more

Thomas Engelhardt is a Researcher and PhD student at the Computer Graphics Group of the Karlsruhe Institute of Technology (KIT) , Germany. His work focuses on real-time rendering techniques, including global illumination, participating media, and visibility culling. Research Interests: Interactive 3D graphics High-quality lighting simulation GPU-based rendering algorithms Occlusion culling and visibility optimization Participating media rendering Environment mapping techniques Publications demonstrate expertise in virtual point lights, epipolar sampling, hierarchical buffers, and scalable final gathering for global illumination.

Jonas UngerView profile

Professor

• Computer Graphics
• Image Processing
• Artificial Intelligence
• +3 more

Jonas Unger is a Professor at Linköping University's Department of Engineering and Natural Sciences (ITN) and Media and Information Technology (MIT). As a research leader in computer graphics and image processing, he contributes to advanced visualization techniques, GPU computing, and AI applications in healthcare and climate adaptation. Specializes in BRDF modeling, spectral light field imaging, and augmented intelligence Active in AI4Climateadaptation and Wallenberg Autonomous Systems Program (WASP) Recipient of the 2023 Chester Carlson Research Prize Develops AI methods for medical imaging (SCAPIS dataset) and autonomous systems His recent work focuses on deep learning for material acquisition, real-time rendering optimizations, and visual analytics pipelines for disaster response systems. Current projects include multi-agent reinforcement learning for air traffic control and GPU-accelerated signal processing techniques. Scientific awards include: Chester Carlson Research Prize (2023) He collaborates with Visual Sweden's Augmented Intelligence platform, co-leads major visualization conferences, and contributes to Horizon 2020 Marie Skłodowska-Curie funded research. Contact: jonas.unger@liu.se

• Artificial Intelligence
• Computer Vision
• Domain Adaptation
• +6 more

Tatiana Tommasi is an Associate Professor at the Department of Control and Computer Science (DAUIN) at Polytechnic University of Turin, actively contributing to advanced AI research and education. She serves as Deputy Coordinator of the National Doctoral College in Artificial Intelligence and Scientific Advisor for the European AI, Data, and Robotics Association (ADRA) and ELLIS Network. Her affiliations include the SmartData@PoliTO Laboratory and VANDAL Visual and Multimodal Applied Learning Laboratory. Her research focuses on algorithm fairness, computer vision, domain adaptation, autonomous driving, and robot learning. Recent work includes improving neural network reliability through fault-aware design, 3D semantic novelty detection, and visual relationship reasoning for robotic grasp planning. She has contributed to European research projects like ELSA (Secure and Safe AI) and commercial initiatives in space technologies and autonomous vehicle uncertainty quantification. Selected 2024-2025 publications demonstrate expertise in foundation models, fairness metrics, uncertainty estimation, and geometric deep learning. Her team leads commercial research projects on industrial robotics trajectory generation and satellite data analysis. She teaches core courses in Computer Engineering, Automotive Engineering, and Data Science, mentoring PhD students in Artificial Intelligence and Computer Systems Engineering. Research keywords: Artificial Intelligence, Machine Learning, Computer Vision, Domain Adaptation, Robot Learning, Transfer Learning, Fairness in AI, Uncertainty Quantification, Autonomous Driving, 3D Point Cloud Analysis, Vision Transformers, Industrial Robotics.

Tobias IsenbergView profile

Researcher

• Scientific Visualization
• Computer Graphics
• Human-Computer Interaction
• +5 more

Tobias Isenberg is a Senior Research Scientist (Directeur de recherche) at Inria's AVIZ project group in Saclay, Université Paris-Saclay. He is affiliated with the Johann Bernoulli Institute for Mathematics and Computer Science at the University of Groningen, Netherlands. His research focuses on interactive scientific visualization, illustrative rendering techniques, and human-computer interaction in non-traditional environments like AR/VR. He has pioneered methods for blending dynamic data physicalizations with virtual content and enhancing collaborative AR learning. Key contributions include machine learning-driven visualization tools for cell lineage analysis and perceptually grounded evaluation frameworks for visualizations. His work spans medical visualization, educational AR systems, and reproducibility in visualization research. He has collaborated with institutions such as the Interactive Media Lab Dresden and led projects like Naviscope (Inria) and tVISt (ANR/DFG). Recent awards include the 2024 SciVis Test-of-Time Award for his 2012 selection techniques paper and a Best Paper Award at CHI 2025 for AR transition techniques. He currently seeks a PhD student to advance interactive 3D dataset exploration methods. Notable grants include the tVISt collaboration grant (2024) and institutional funding from Inria. His lab, AVIZ, develops open-source tools like LineageD+ for biological data analysis and interactive physicalization systems. Recent publications emphasize cross-reality visualization, human-AI collaboration, and reproducibility in visualization research.

Karan Sher SinghView profile

Professor

• Computer Graphics
• Human-Computer Interaction (HCI)
• Artificial Intelligence
• +4 more

Karan Sher Singh is a Professor in the Department of Computer Science at the University of Toronto, affiliated with the Dynamic Graphics Project (DGP) laboratory. His research focuses on interactive computer graphics, human-computer interaction, and artificial intelligence, with applications in sketch-based interfaces, character animation, and immersive technologies like AR/VR. He has pioneered tools such as Meshmixer, CrossShade, and JALI Research, which have been adopted in industries including film (e.g., Weta Digital’s Avatar: The Way of Water) and gaming (Cyberpunk 2077). Education and Background: Completed his PhD in 1994, working on early virtual teleconferencing systems at ATR. His work bridges artistic expression, technical innovation, and perceptual principles to create intuitive design tools. Research Interests: Sketch and sculpt interfaces for 3D modeling and design Facial and character animation (INCA) for films and games Mathematical surface representations for conceptual design Augmented/VR storytelling and immersive environments (e.g., JanusXR) Artistic projection and non-photorealistic rendering Recent Work Trends: Articles from 2016–2023 emphasize VR/AR interaction, immersive design tools, and anatomically based animation. His research often integrates HCI principles with geometric algorithms to address challenges in freehand sketching, mid-air gestures, and musculoskeletal modeling. Awards and Recognitions: Best Paper Awards at SBIM (2008, 2012, 2014) Technology Transfer Awards from MITACS NCE (2003–2012) VFX Oscar-winning contribution via Weta Digital Advising and Industry: Supervised over 20 graduate students, many contributing to tech companies like Pixar, Google, and EA. Co-founded JALI Research, JanusVR, and collaborated with industry leaders such as SideFX, NVIDIA, and NVIDIA. Labs and Teams: Leads the DGP lab, fostering cross-disciplinary projects between academia and industry. Active in developing open-source tools like JanusXR and Meshmixer.

• Nuclear Engineering
• Reactor Physics
• Fuel Cycle Modeling
• +3 more

Madicken Munk is an Adjunct Assistant Professor in the Department of Nuclear, Plasma, and Radiological Engineering at the University of Illinois' College of Engineering. She specializes in nuclear energy systems, reactor modeling, and computational tools for fuel cycle analysis. Her work emphasizes open-source software development, particularly with the yt platform for data visualization and analysis. Research interests include reactor physics, advanced reactor design (e.g., pebble-bed fluoride salt-cooled reactors), and hybrid computational methods for radiation transport. She has contributed to projects such as the Mark-I PB-FHR reactor and HALEU fuel cycle dynamics. Recent work focuses on yt 4.0 enhancements and sensitivity analysis of nuclear fuel transitions. Publications span reactor simulation, data visualization, and planetary geochronology instrumentation. Collaborations include FHR test reactor design and open-source tool development for scientific workflows. No scientific awards are listed, but her contributions to computational frameworks and reactor modeling are notable. Teaching includes courses on nuclear energy systems (NPRE 247) and reactor theory (NPRE 555). Active in FHR development and computational infrastructure for nuclear engineering applications.

• Computer Graphics
• Machine Vision
• Artificial Intelligence
• +5 more

Dr Farshad Einabadi is a Senior Research Engineer at the Centre for Vision, Speech and Signal Processing (CVSSP) , University of Surrey, and contributes to the CoSTAR National Laboratory . His work focuses on neural rendering, real-time systems, and media personalization within the intersection of computer graphics, machine vision, and AI. Research interests include lighting/illumination applications (acquisition, modeling, rendering), virtual production tools, and industrial sensor calibration. He leads projects in next-gen UK screen technologies infrastructure (UKRI AHRC CoSTAR) and has contributed to EPSRC AI4ME and EU FP7 Dreamspace initiatives. Publications emphasize datasets like ForecasterFlexOBM (multi-view audio-visual) and 3DVHshadow , advancing human avatar rendering and cast shadow generation. He teaches AI Bootcamp for the UKRI CDT in Digital Media Inclusion and reviews for Eurographics and top-tier conferences. Industry experience includes software engineering for real-time augmented reality systems. Collaborates in labs/teams at CVSSP and CoSTAR, advancing projects in virtual production and immersive media technologies.

Nils DahlströmView profile

Associate Professor

• Medical Imaging
• Quantitative MRI
• Low-Dose CT Techniques
• +3 more

Nils Dahlström is an Associate Professor and Head of Unit at Linköping University's Department of Health, Medicine and Caring Sciences (HMV), within the Division of Diagnostics and Specialist Medicine (DISP). His primary affiliation is the Unit of Radiological Sciences, where he focuses on advancing medical imaging techniques and their clinical applications. He holds a Medical Degree from Uppsala University (1997), became a licensed medical practitioner (1998), specialized in Diagnostic Radiology (2003), and earned a PhD in Medical Radiology from Linköping University (2010). His research emphasizes hepatobiliary applications of quantitative contrast-enhanced MRI for assessing liver diseases, including chronic liver monitoring and pre-operative liver function evaluation. He also investigates low-dose CT imaging techniques and dual-energy CT applications. Additional interests include medical visualization technologies, such as 3D volume rendering on the Sectra platform, and educational strategies in medical imaging. He has contributed to projects like the ACCESS-ESLD study and EPSONIP study, addressing liver disease surveillance and NAFLD prevalence in primary care. Dr. Dahlström’s work bridges clinical practice and research, aiming to improve diagnostic accuracy and patient outcomes through innovative imaging methods. His interdisciplinary approach includes collaborations in computational modeling, radiation safety, and medical education. He actively participates in initiatives like the Center for Medical Image Science and Visualization (CMIV), fostering advancements in image analysis and visualization for healthcare.

Patric LjungView profile

Associate Professor

• Visualization Technologies
• Software Design
• Medical Imaging
• +4 more

Patric Ljung is an Associate Professor at Linköping University, affiliated with the Media and Information Technology (MIT) division within the Department of Science and Technology (ITN). He leads the Immersive Visualization group and has been a key figure in research projects focusing on visualization technologies, software design, and medical imaging applications. Previously, he worked at Siemens Corporation in the U.S., contributing to medical visualization tools and quality management. Dr. Ljung holds an M.S. in Information Technology (2000) and a Ph.D. in Scientific Visualization (2006) from Linköping University. His research focuses on large-scale visualization technologies, software architecture for visualization systems, and direct volume rendering. Current projects explore heterogeneous data management, data provenance, and unification of transfer functions. He emphasizes immersive visualization techniques for applications in healthcare, planetary science, and public engagement through collaborations with institutions like the Visualization Center C. With over 40 peer-reviewed publications and seven patents, his work spans medical visualization, augmented reality, and interactive systems. Recent trends include leveraging immersive technologies for climate change communication and autonomous systems visualization. He has directed projects such as C-research, coordinating visualization efforts with the Visualization Center C. His leadership includes roles as head of the Immersive Visualization group and former director of C-research. Collaborations with Siemens and the Visualization Center C highlight his interdisciplinary approach.

Manmohan ChandrakerView profile

Professor

• Computer Vision
• 3D Reconstruction
• Scene Understanding
• +5 more

Manmohan Chandraker is a Professor in the Department of Computer Science & Engineering at the University of California, San Diego (UCSD). His research focuses on computer vision, 3D reconstruction, and autonomous driving, with interdisciplinary links to robotics, machine learning, and computer graphics. He leads projects in 3D scene understanding, real-time visual odometry, and sensor fusion for autonomous systems. His work has been recognized with top academic awards and industry accolades. Education: B.Tech. in Electrical Engineering from IIT Bombay Ph.D. in Computer Science from UCSD Postdoctoral scholarship at UC Berkeley Research Interests: Chandraker’s work addresses challenges in 3D reconstruction under complex lighting and materials, autonomous driving systems, and physically-based inverse rendering. Key contributions include frameworks for non-convex optimization in geometric reconstruction and semantic-driven dense reconstruction techniques. His research bridges theory and practice, with applications in augmented reality, robotics navigation, and automotive safety systems. Key Awards: Best Paper Award at CVPR 2014 UCSD CSE Dissertation Award (2009) NEC Business Contribution Award (2015) Advising & Industry Collaboration: He has led teams at NEC Labs America, collaborating with automobile manufacturers to develop single-camera systems for real-time autonomous driving. His work on closed-loop traffic simulations and adversarial scenario generation has driven industry partnerships and patents. Current research explores multimodal LLM integration, data-centric AI tools (e.g., Ymir platform), and photorealistic scene synthesis. Labs & Projects: Chandraker’s group develops open frameworks like OpenRooms and TRoVE for 3D scene datasets, and contributes to benchmarks for domain adaptation in vision tasks. His team also works on safety-critical systems for autonomous vehicles through projects like SAFE-SIM and Drive-1-to-3.