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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.

• 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.

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.

• Machine Learning
• Renewable Energy
• Quantum Computing
• +5 more

Dr. Hao Chen is an Assistant Professor at the University of Twente, affiliated with the Industrial Engineering & Business Information Systems department and the MESA+ Institute. His research focuses on renewable energy systems, machine learning applications, and autonomous systems, contributing to the United Nations Sustainable Development Goals. Dr. Chen's research interests include wind energy modeling, quantum computing for energy systems, vehicular edge computing, and trajectory prediction in autonomous driving. He explores machine learning techniques for fault detection in energy infrastructure and develops innovative solutions for sustainable energy scenarios. His work also addresses human-machine interaction in autonomous vehicles and environmental monitoring systems. His recent publications explore advancements in computer vision techniques for scene graph prediction, building outline extraction, and camera pose estimation. He has also contributed to studies on energy systems, including wind model downscaling, quantum computing applications, and cost-efficient vehicular edge computing for air pollution monitoring. His work bridges theoretical developments with practical applications in sustainable energy and autonomous technologies. No scientific awards or advising/grant information is available. His research aligns with the university's focus on sustainable innovation and technological solutions.

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.

Laszlo A. JeniView profile

Assistant Professor

• Computer Vision
• Digital Humans
• Computational Behavior Science
• +6 more

Laszlo A. Jeni is an Assistant Research Professor at Carnegie Mellon University's Robotics Institute, leading the Computational Behavior (CUBE) Lab. His research focuses on computer vision, digital humans, and computational behavior science, with applications in healthcare, affective computing, and assistive technologies. He develops methods to model human behavior using multi-modal sensors, including facial, body, and physiological data. Current research emphasizes human motion synthesis, clinical movement analysis, and 3D scene reconstruction. Key research topics include action recognition for clinical applications, generative models for 4D scene synthesis, and video-based physiological estimation. Jeni supervises a team of PhD and master's students in the CUBE Lab, advancing interdisciplinary projects at the intersection of AI and behavioral science. His work has led to innovations in non-contact health monitoring and virtual avatar control systems. Notable contributions include frameworks for sim-to-real transfer in human mesh recovery, diffusion-based camera alignment, and video transformers optimized for efficiency. Jeni's lab actively participates in challenges like the V4V (Vision for Vitals) initiative and benchmarks for 3D facial alignment, maintaining a strong presence in both academic and applied computer vision communities.

Dongyeon KimView profile

Researcher

• Augmented Reality (AR)/Virtual Reality (VR)
• Computational Optics
• 3D/4D Displays
• +3 more

Dongyeon Kim is a Researcher at the University of Cambridge's Department of Computer Science and Technology, collaborating with Prof. Rafal Mantiuk. She holds a Ph.D. in Electrical and Computer Engineering from Seoul National University (SNU), where she contributed to the Optical Engineering and Quantum Electronics Lab under Prof. Byoungho Lee. Her work focuses on bridging computational optics with visual perception, particularly in next-generation AR/VR displays, holographic systems, and 3D display technologies. Education: Ph.D., Electrical and Computer Engineering, Seoul National University (2023) Bachelor's Degree, Electrical and Computer Engineering, Seoul National University (20XX) Research Interests: Augmented/Virtual Reality (AR/VR) display systems Holographic display optimization and human perception modeling Computational optics for 3D/4D displays Visual perception evaluation and quality metrics Integration of machine learning in display technology Awards & Recognition: Sejong Science Fellowship Grant (Korean Government) Best Paper Honorable Mention at SIGGRAPH Asia 2024 Grants & Funding: Sejong Science Fellowship for postdoctoral research Lab & Team: Collaborates with Prof. Mantiuk's research group at the University of Cambridge, focusing on perceptual evaluation of AR displays and dataset development (e.g., AR-DAVID).

Eckehard SteinbachView profile

Professor

• Haptic Communication
• Tactile Internet
• Multimedia Systems
• +4 more

Prof. Dr.-Ing. Eckehard Steinbach is a Full Professor of Media Technology at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology. His research focuses on haptic communication, the Tactile Internet, multimedia systems, and machine learning-driven analysis of sensory data. He holds an IEEE Fellowship (2015) for contributions to visual and haptic communications and has led projects like the Centre for Tactile Internet with Human-in-the-Loop (CeTI). Education: Studied Electrical Engineering at the University of Karlsruhe, University of Essex, and ESIEE Paris. Earned a Ph.D. from Friedrich-Alexander University of Erlangen-Nuremberg (1999). Postdoc at Stanford University (2000–2002). Research Interests: Haptic data compression, teleoperation, networked multimedia systems, and applications of machine learning in sensory data analysis. Key projects include the IEEE 1918.1.1-2024 standard for haptic codecs and 5G-based teleoperation systems. Awards: ERC Starting Grant (2011–2015), Alcatel-Lucent Research Award (2011), VDE-ITG Publication Award (2009). Grants and Projects: Led initiatives in tactile internet, 5G testbeds for eHealth, and radar-based human activity monitoring. Collaborates on robotics and remote collaboration systems via platforms like the Munich 5G Research Hub. Labs/Teams: Chair of Media Technology at TUM, contributing to TUM-IAS and the Munich Institute of Robotics and Machine Intelligence (MIRMI).

• 3D Computer Vision
• Computer Graphics
• Machine Learning
• +5 more

Dimitris Tzionas is an Assistant Professor for 3D Computer Vision at the University of Amsterdam (UvA), leading research in the intersection of Computer Vision, Computer Graphics, and Machine Learning. His work focuses on modeling human-object interactions, 3D/4D perception, and synthesis for applications in Ambient Intelligence, Virtual Assistants, and the Metaverse. He holds an ERC Starting Grant (€1.5M) and ELLIS Amsterdam affiliations. Previously, he was a Research Scientist at Max Planck Institute for Intelligent Systems (MPI-IS), contributing to projects like the GRAB dataset and MANO/SMPL body models. He earned his PhD from the University of Bonn on hand-object interaction, advised by Jürgen Gall, and completed his MSc at Aristotle University of Thessaloniki in Electrical & Computer Engineering. His research has produced impactful datasets (e.g., GRAB, InterCap, DAMON) and methods like InteractVLM and PICO, advancing human-centric AI. He actively serves on CVPR/ICCV/ECCV committees and teaches 'Introduction to Computer Vision' at UvA. Notable awards include NVIDIA grants, Google Research Gifts, and multiple Outstanding Reviewer recognitions. His lab collaborates widely, advising over 10 PhD/MSc students and postdocs, with projects funded by ERC, ELLIS, and industry partners like NVIDIA and Google. Key themes include 3D reconstruction, interaction modeling, and generative AI for realistic avatar creation.

Andreas PaulView profile

Researcher

• Computer Graphics
• Real-Time Visualization
• Computational Geometry
• +3 more

Andreas Paul is a Researcher affiliated with the Department of Computer Science (Informatik V) at the Technische Universität München (TUM), part of the TUM School of Computation, Information and Technology. His research focuses on real-time visualization, computational geometry, and flight simulation systems. He contributed to the FORTWIHR project, developing synthetic vision systems for aircraft, demonstrating expertise in adaptive algorithms and terrain triangulation. Collaborations include work with the TU Braunschweig and ESG, highlighting interdisciplinary engagement. His academic background includes a Master's thesis (1995) and a PhD dissertation (2000) on hierarchical data structures and terrain modeling. Professional activities include conference participation and contributions to visualization technology for aviation applications. Education: PhD in Computer Science, TU Munich, 2000 Master's Thesis: 'Compression of image sequences with hierarchical bases', 1995 Research interests emphasize practical applications of computational methods in aviation and geospatial systems, with a strong focus on real-time performance and algorithmic efficiency. His work bridges computer graphics, geographic information systems, and aerospace engineering, addressing challenges in synthetic vision and terrain data representation.

Olga GutanView profile

Researcher

• Computer Graphics
• Geometry Processing
• Algorithm Design
• +1 more

Olga Gutan is a doctoral student at Carnegie Mellon University 's Computer Science Department , affiliated with the Geometry Collective and advised by Keenan Crane . Her work focuses on computer graphics and geometry processing , with a primary research interest in vectorization and surface algorithm development. Current role: Doctoral Research Assistant Past work: Nonmanifold Minimal Surfaces with mentors Etienne Vouga, Nicholas Sharp, Josh Vekhter Her research bridges theoretical geometry and practical implementation, with publications on singularity-free frame fields for vectorization and exploratory work on gravitational surface rendering in Houdini. She received an Honorable Mention for Best Paper at Symposium on Geometry Processing 2023. Olga contributes to algorithm development and visualization techniques, including triply-periodic nonmanifold surfaces. Scientific Awards : Best Paper (Honorable Mention), Symposium on Geometry Processing 2023 Key Collaborations : Mentored by Etienne Vouga, Nicholas Sharp, and Josh Vekhter during summer 2021. Affiliated with the Geometry Collective at Carnegie Mellon.

Farnam JahanianView profile

Professor

• Computer Animation
• Robotics
• Dynamic Systems Control
• +2 more

Farnam Jahanian is President and Professor of Computer Science and Robotics at Carnegie Mellon University. His research develops algorithms for controlling dynamic physical systems in robotics and animation, including human motion synthesis, robotic manipulation, and simulated clothing/fluid dynamics. Current work explores motion planning for humanoid robots using motion capture data and physical simulations. Recent publications (2024-2025) focus on kinematic motion retargeting, volumetric hairstyle capture, synthetic data for action recognition, and facial expression translation for robots. His lab integrates computer graphics with robotics to create realistic virtual characters and adaptive control systems.

• Computer Vision
• 3D Reconstruction
• Neural Rendering
• +5 more

Dr. Miaomiao Liu is a Research Fellow at the School of Computing, The Australian National University. Her research focuses on computer vision, 3D reconstruction, and neural rendering, with applications in robotics, autonomous systems, and renewable energy forecasting. She leads multiple projects including Next-Generation Aviation Safety Net Air Traffic Management, Machine Vision Techniques for Solar Power Forecasting, and 3D Vision Geometric Optimization in Deep Learning. Her work integrates cutting-edge techniques such as neural radiance fields, depth estimation, and self-supervised learning to address challenges in dynamic scene reconstruction, motion forecasting, and image deblurring. She has pioneered methods for mining supervision signals in dynamic regions and developing language-driven deblurring networks. Key Projects: Aviation safety systems, solar irradiance prediction, and geometric optimization in deep learning Research Themes: 3D scene understanding, human motion prediction, and neural rendering Technical Expertise: Neural networks, multi-view stereo, and physics-based modeling Dr. Liu's research has been published in top-tier venues like CVPR and IEEE conferences, with over 2,450 citations. While not explicitly listed as part of a lab, her work demonstrates strong collaboration with industry partners such as CSIRO and aerospace stakeholders. She actively supervises research students in areas like 3D vision and energy systems.

• Computer Graphics
• Computer Vision
• Machine Learning
• +7 more

Corey Toler-Franklin is an Assistant Professor in the Computer Science Department at Barnard College, Columbia University, directing the Graphics, Imaging & Light Measurement Lab (GILMLab). Her research focuses on computer graphics, vision, and machine learning applications in biomedical research, oncology, and archaeology. She holds a Ph.D. in Computer Science from Princeton University and has held positions at UC Davis, Adobe, and Google. Education: Ph.D., Computer Science, Princeton University (2011) M.S., Architecture & Computer Graphics, Cornell University (2000) B.Arch., Cornell University (1999) Research Interests: Developing algorithms for capturing and analyzing complex materials' shape/appearance through optics principles. Applications include diagnosing metastatic cancers, studying neurological disorders, and restoring cultural heritage artifacts. Expertise spans machine learning, multispectral imaging, and non-photorealistic rendering. Awards: 2009 Google Anita Borg Award NSF iDigBio Visiting Scholar (2013) First African American Ph.D. in Computer Science at Princeton Grants & Labs: Leads GILMLab, collaborating with oncology/pathology experts. Former UC President’s Postdoctoral Fellow. Active in 3D digitization projects for STEM education and museum conservation. Labs/Teams: Graphics, Imaging & Light Measurement Lab (GILM Lab) at Barnard, previously affiliated with UC Berkeley CITRIS Banatao Institute.