Find Academic Supervisors

• Virtual Reality
• Human-Computer Interaction
• Educational Technology
• +3 more

Christoph W. Borst is a professor at the University of Louisiana at Lafayette, USA, specializing in Virtual Reality (VR) and Human-Computer Interaction (HCI). His research focuses on enhancing educational VR environments through attention guidance, emotion recognition, and multimodal sensing (EEG, eye-tracking). He collaborates with researchers like Jason Woodworth, Adil Khokhar, and Arun Kulshreshth on projects involving spatial interaction, distraction classification, and pedagogical agents. His work includes developing time-continuous emotion rating interfaces, gaze-driven attention restoration systems, and VR tools for teaching molecular reactions and geosciences. Key publications address VR classroom monitoring, collaborative dataset exploration, and haptic feedback optimization for precision tasks. Articles highlight applications in rehabilitation, energy education, and simulated welding training. Research interests span VR attention mechanisms Emotion detection in immersive environments Machine learning for student distraction classification Interactive 3D visualization techniques

• Computer Vision
• Image Processing
• Machine Learning
• +5 more

Hao Gao is a Professor in the Department of Computer and Information Science at the University of Macau, Faculty of Science and Technology. His research spans computer vision, image processing, and machine learning with a particular focus on human pose estimation, 3D reconstruction, and optimization algorithms. He maintains strong collaborative ties with Nanjing University of Posts and Telecommunications in China, reflecting a dual institutional affiliation that enhances his research impact across Greater China. His research interests center on computer vision and artificial intelligence, with significant contributions in human pose estimation, 3D reconstruction, point cloud processing, and optimization algorithms. Dr. Gao's work on skeleton-based action recognition, scene flow estimation, and neural rendering techniques has established him as a leading researcher in these specialized areas. His recent work on GaussianHead for high-fidelity head avatars and lifespan age synthesis demonstrates his ability to bridge theoretical advances with practical applications in digital human representation. Dr. Gao's publication record shows a clear evolution from foundational work on artificial bee colony algorithms to cutting-edge research in neural rendering and 3D vision. His recent publications (2023-2025) demonstrate a strong focus on human-centric computer vision problems, including pose estimation, motion prediction, and medical applications for Parkinson's disease assessment. The interdisciplinary nature of his work connects computer vision with healthcare applications, autonomous systems, and virtual reality. Dr. Gao has mentored numerous graduate students who have become productive researchers in their own right, including Haolun Li, Jiucheng Xie, and Jian Xiong who frequently appear as co-authors on his publications. His research group has secured funding for projects related to human motion analysis, medical image processing, and autonomous driving perception systems. His laboratory focuses on advancing computer vision techniques for human understanding, with recent projects including skeleton-based action recognition systems, Parkinson's disease assessment tools, and high-fidelity digital avatar creation. The team maintains strong industry connections, particularly in applications related to autonomous vehicles and medical diagnostics.

Eric BrachmannView profile

Researcher

• Computer Vision
• Machine Learning
• Object Pose Estimation
• +5 more

Dr. Eric Brachmann is a Researcher at Heidelberg University 's Visual Learning Lab (since 2017) and a Guest at Leibniz University Hannover (since 2019). He earned his Dr. rer. nat. in 2018 from TU Dresden (summa cum laude), preceded by a Diplom in media computer science (2012) and studies (2006–2012) at TU Dresden. Doctorate: TU Dresden (2018, summa cum laude) Diplom: TU Dresden (2012, passed with distinction) Education: Media and computer science (2006–2012) His research focuses on Computer Vision and Machine Learning , particularly 6D object pose estimation , camera localization , and neural-guided optimization . His work bridges classical geometric methods (e.g., RANSAC) with modern deep learning techniques, including differentiable optimization and reinforcement learning for pose estimation. His publications emphasize end-to-end learning , robust model fitting , and RGB-D image analysis , with applications in robotics and 3D scene understanding. Key contributions include DSAC, CONSAC, and neural extensions of RANSAC for efficient hypothesis sampling. 2018 : GI Dissertation Award nomination 2014 : ACCV Honorable Mention Demo Award 2012 : Enno Heidebroek Award for top graduate 2008–2012 : German National Academic Foundation scholarship 2008 : IBM Award for intermediate diploma As a co-organizer of ICCV and ECCV workshops, Eric drives collaboration in visual localization and 6D pose estimation . He has reviewed for CVPR, ICCV, NeurIPS, and TPAMI, earning recognition as an Outstanding Reviewer (CVPR 19, NeurIPS 19). He has held industry roles at IBM (2010–2011) and T-Systems (2008–2009). At TU Dresden and Heidelberg, he taught courses on computer vision and 3D world reconstruction , supervised theses, and developed practical seminars.

André StorkView profile

Professor

• Computer Graphics
• Computer-Aided Design (CAD)
• Simulation
• +4 more

Prof. André Stork is a Professor at Technische Universität Darmstadt and Industry Director (Automotive) at Fraunhofer IGD. He holds a PhD in Computer Science (2000) and a diploma (1992) from TU Darmstadt. His research focuses on geometry modeling/processing, 3D interaction, simulation, and visualization. He leads projects in automotive/ manufacturing industries, coordinating over 200 R&D initiatives. His work emphasizes real-time simulation, CAD-AM integration, and GPU-based algorithms. Education: PhD in Computer Science (TU Darmstadt, 2000) Key Roles: Department Head (2002–2023), Editor-in-Chief of IEEE CG&A Research interests include graded multi-material CAD, iso-geometric analysis, and interactive design tools. He has authored/co-authored 200+ papers (h-index 25), focusing on fields like real-time rendering, mesh processing, and Industry 4.0 applications. Recent articles highlight trends in GPU-accelerated simulation, digital twin technologies, and metaverse infrastructure. His work bridges academia and industry, addressing challenges in additive manufacturing and virtual prototyping. Students advised: 6 doctoral/master’s students (e.g., Daniel Ströter, Christian Altenhofen) Key Projects: GraMMaCAD, CloudiFacturing, and Industry 4.0 studies He chairs conferences like VAST and serves on editorial boards for journals including IEEE CG&A and Applied Sciences.

• Computer Graphics
• CAD Systems
• Geometric Modeling
• +2 more

Ioannis Fudos is Professor and former Chair (2014-2018) of the Computer Science and Engineering Department at the University of Ioannina. He holds a Diploma in Computer Engineering from University of Patras, and MS/PhD degrees in Computer Science from Purdue University. His research spans computer graphics, CAD systems, geometric modeling, animation, and image retrieval. He directs the Computer Graphics Research Group and has secured substantial funding (€2M+) from European and national sources for 17+ projects. His scholarly contributions include publications in top venues (SIGGRAPH, Eurographics, IEEE TVCG) covering rendering techniques, 3D printing quality control, assistive technologies, and cultural heritage digitization. Recent work explores neural rendering transparency methods, wheelchair navigation interfaces, and pedestrian routing algorithms. His laboratory maintains a repository of 3D models for research use.

Ling-Qi YanView profile

Associate Professor

• Computer Graphics
• Rendering Algorithms
• Real-time Ray Tracing
• +5 more

Ling-Qi Yan is an Associate Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB), where he co-directs the MIRAGE Lab and is affiliated with the Four Eyes Lab. His research focuses on computer graphics, particularly real-time rendering, physically-based appearance modeling, and advanced light transport algorithms. Prior to UCSB, he earned his PhD from UC Berkeley, advised by Ravi Ramamoorthi, and completed internships at Disney, Autodesk, Weta Digital, and NVIDIA Research. He also holds a B.E. in Computer Science from Tsinghua University. Yan's education includes a PhD in Computer Science from UC Berkeley (2018) and a B.E. from Tsinghua University (2013). His research interests span rendering photo-realistic visuals, real-time ray tracing, and appearance modeling for materials like fabrics and fur. Notable achievements include the 2023 EGSR Best Paper Award for cloth shading work and the 2019 ACM SIGGRAPH Outstanding Doctoral Dissertation Award. His awards include the Regents' Junior Faculty Fellowship (UCSB), Best Visual Effects Award (EGSR 2023), and NVIDIA Graduate Fellowship supervision recognition. He teaches courses such as Introduction to Computer Graphics and Real-Time High-Quality Rendering , and has developed online courses in Chinese like GAMES101 and GAMES202 . Yan's lab collaborations and industry ties include roles as a research consultant at Intel and visiting professor at NVIDIA. His research emphasizes bridging theory and practice, with over 50 publications in top venues like SIGGRAPH and ACM Transactions on Graphics.

Reinhold PreinerView profile

Researcher

• 3D Computer Graphics
• Visualization
• Geometry Processing
• +3 more

Reinhold Preiner is a Senior Researcher at the Institute for Computer Graphics and Knowledge Visualization, part of the Faculty for Computer Science and Biomedical Engineering at TU Graz. He holds a PhD from TU Wien (2017) focused on dynamic and probabilistic point-cloud processing. His research emphasizes 3D graphics, geometry processing, and cultural heritage digitization. Current projects include Open Reassembly (fragment assembly for archaeological artifacts) and VR4CPPS (virtual reality in production systems). Education: PhD in Computer Science, TU Wien (2017) Dipl.-Ing. (MSc equivalent) in Computer Science, TU Wien Research Interests: Probabilistic geometry processing, interactive visualization, cultural heritage preservation through digital methods, and VR applications. Recent work includes thermal conduction modeling in astrophysical systems and crowd simulation algorithms. Projects & Grants: FWF Research Group A+CHIS (Cultural Heritage Informatics) Collaborative projects with Fraunhofer Institute Labs/Teams: Leads the Visual Computing group at TU Graz, collaborating with international partners on cultural heritage digitization and VR solutions.

• Computer Vision
• Deep Learning
• Biomedical Signal Processing
• +4 more

David Fuentes Jiménez is a Researcher at the Department of Electronics, Universidad de Alcalá, Spain. He is affiliated with the GEINTRA research group focusing on Electronic Engineering applied to Intelligent Spaces and Transport. His doctoral thesis (2021) explored deformable object reconstruction using deep learning techniques, supervised by Dr. Daniel Pizarro Pérez. His research spans computer vision, biomedical signal processing, and smart environments. Key research interests include neural radiance fields in surgery, photoplethysmographic signal dynamics for physiological assessment, and real-time action recognition using depth data. He has contributed to EU projects like GEMS through sensory module development (Ruby). His work integrates deep learning with 3D reconstruction, wearable sensors, and overhead camera systems. Publications highlight innovation in medical imaging, stress detection via PPG signals, and robust people detection algorithms. His work frequently appears in top venues, showcasing interdisciplinary approaches between computer science, biomedical engineering, and robotics. Active in open datasets like GOTPD1, he bridges theory and practical applications in smart spaces and healthcare technology. Education: PhD in Electronics Engineering (2021), Universidad de Alcalá Labs/Teams: GEINTRA Group

Raffaele De AmicisView profile

Associate Professor

• Virtual Reality
• Augmented Reality
• Human-Computer Interaction
• +7 more

Raffaele De Amicis is an Associate Professor at the School of Electrical Engineering and Computer Science , Oregon State University. With a PhD in Industrial Engineering from the University of Bologna (2001) and a professional engineering license (1997), he bridges technical expertise with immersive technology applications. His career spans roles at Fraunhofer Institute (1999-2002), founding directorship of GraphiTech in Trento, Italy, and consulting professorship at the University of Trento (2003-16). Degrees: Ph.D., Design and Methods of Industrial Engineering, University of Bologna M.S., Mechanical Engineering, University of Calabria Professional Engineer License, Italian Charter Research focuses on Virtual Reality , Augmented Reality , and Human-Computer Interaction , particularly for industrial training, geospatial visualization, and educational applications. His work on digital twins, immersive engineering instruction, and XR-based disassembly systems demonstrates interdisciplinary impact. Scientific contributions include over 120 publications, three books, and 15 edited texts. Key projects involve VR safety training for confined spaces, AI-augmented AR guidance, and forest digital twin frameworks. Articles span 2012-2025, emphasizing 3D visualization , multimodal interfaces , and smart manufacturing . Scientific Leadership: Vice-President, GraphicsMedia.net (2010-present) Project Coordinator for EC/NATO/industry grants (€20M total) Founder, GraphiTech Research Center His expertise in multinational research coordination and technology transfer has shaped collaborations across Europe, with applications in forestry, urban planning, and hazardous environment training.

• Data Visualization
• Scientific Visualization
• Computer Graphics
• +6 more

João Luiz Dihl Comba is a Professor at the Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Brazil. With a PhD in Computer Science from Stanford University (1993-2000) under advisor Leonidas J. Guibas, he has established himself as a leading researcher in visualization and computer graphics. His academic journey includes a M.Sc. in Systems Engineering and Computing from UFRJ (1988-1991) and a B.Sc. in Computer Science from UFRGS (1983-1987), along with a sabbatical at the University of Utah (2010-2011). Comba's research focuses on data and scientific visualization, visual analytics, computer graphics, and their applications in medical imaging, sports analytics, and pandemic response. His work bridges theoretical advances in multidimensional projections with practical applications in healthcare, oil and gas, and digital twins. Recent publications demonstrate his continued leadership in applying machine learning techniques to visualization problems, particularly in biomedical contexts. His publication record spans over three decades with consistent output through 2025, showing evolution from foundational computer graphics work to contemporary applications of AI in visualization. The publications reveal strong collaborations with researchers across Brazil and internationally, with particular emphasis on solving real-world problems through visual analytics. As an advisor, Comba has mentored numerous graduate students who have become active researchers in visualization and computer graphics, with several continuing to collaborate with him on publications. His research group at UFRGS appears to be particularly strong in medical visualization applications, as evidenced by multiple recent publications related to COVID-19 analysis and medical image processing.

• Human Computer Interaction (HCI)
• Virtual and Augmented Reality
• Gamification Technology
• +5 more

Professor Manolya Kavakli-Thorne is a distinguished academic at Aston University, holding dual appointments as Professor of Gamification and Simulation Technology in the College of Engineering and Physical Sciences and the Digital Futures Institute. Her interdisciplinary research spans Human-Computer Interaction (HCI), Virtual/Augmented Reality, and Mixed Reality Systems. Currently supervises 3 PhD students and advises 2 others at Aston University, with prior mentorship of 119 postgraduate students. Total research grants exceed £18.1 million, including major projects like the EU-funded Nexus (€392K) and UKRI Diatomic Accelerator (£8M). Her research focuses on applying gamification to emergency management, cybersecurity, and healthcare. Notable achievements include establishing the first Virtual Reality Lab in Sydney (2005) and the Virtual Production Studio in Canberra (2022). Awards include the 2022 Best Paper Award (IEEE) and multiple top-tier conference recognitions. She has authored over 240 refereed papers and pioneered facilities like CEPET (2015) and SIGMA research groups. Professional roles include Guest Editor for Algorithms (2024) and editorial board memberships across 15+ journals. Her work bridges academia and industry through collaborations with institutions like Birmingham City Council and the ACT Government.

Eric PattersonView profile

Associate Professor

• Computer Graphics
• Visual Computing
• Computer Vision
• +12 more

Eric Patterson, Ph.D., is an Associate Professor in Visual Computing at the School of Computing, Clemson University, where he also serves as the Director of the Digital Production Arts (DPA) program. His academic and research work bridges computer science, digital arts, and engineering, with a strong emphasis on visual technologies and creative computation. His research interests span a wide array of topics including physically based material capture and rendering, 3D human face modeling, photogrammetry, computer vision, machine learning in graphics, game development, digital cinematography, and computational arts. These interests reflect an interdisciplinary approach that integrates technical computing with artistic production. The breadth of his work is reflected in the diverse range of courses he has taught, from foundational programming and data structures to advanced topics in rendering, visual effects, technical art direction, and digital production studio. His teaching spans both Clemson University and the University of North Carolina Wilmington (UNCW), where he previously taught courses in computer science, digital media, and film production. Dr. Patterson is affiliated with several key initiatives at Clemson, including the Digital Production Arts program, the Visual Computing Faculty group, and the Charleston Innovation Campus. These affiliations highlight his role in fostering interdisciplinary education and innovation in digital technologies. No scientific awards listed in the provided text. While no formal list of advisees or research grants is provided, his leadership of the DPA program suggests active involvement in student mentorship and collaborative research. He has led seminars on acquiring real-world data for computer graphics, machine learning in graphics, and human face modeling, indicating an ongoing engagement with cutting-edge research topics. He is involved in research related to visual computing and digital production methods, with potential applications in simulation, entertainment, and human-computer interaction. Though no specific lab name is mentioned, his work is closely tied to the Visual Computing research group and the Digital Production Arts program at Clemson University.

Marcus MagnorView profile

Professor

• Computer Graphics
• Computer Vision
• Visual Perception
• +6 more

Prof. Marcus Magnor is a full Professor of Computer Science at Technische Universität Braunschweig (TU Braunschweig), leading the Computer Graphics Lab. He also holds an adjunct professorship in Physics and Astronomy at the University of New Mexico, USA. His academic journey includes a BA in Physics from Würzburg University (1995), an MS from the University of New Mexico (1997), and a PhD in Electrical Engineering from Erlangen University (2000). He completed his habilitation in Computer Science at Saarland University in 2005, earning the venia legendi qualification. His research focuses on visual computing, encompassing image formation, analysis, synthesis, and perception. Key areas include computer graphics, vision, computational photography, astrophysics visualization, and optics. He has pioneered work in multi-view video coding, free-viewpoint video, and planetary nebulae reconstruction. Prof. Magnor has organized over 20 international conferences and workshops, including VMV 2023 and the Symposium on Visual Computing and Perception. He serves on editorial boards for journals like Computer Graphics Forum and has held leadership roles such as CS Department Chair at TU Braunschweig (2015–2019). Awards include the Wissenschaftspreis Niedersachsen and recognition as a Fulbright Scholar. His outreach includes popular science lectures on topics like digital image manipulation and 3D cinema technology.

• 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.

Larry DavisView profile

Professor

• Computer Vision
• Machine Learning
• Visual Surveillance
• +5 more

Larry Davis is a Professor in the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS) at the University of Maryland. He is affiliated with the Computer Vision Laboratory of the Center for Automation Research, where he previously served as head from 1981-1986. His research focuses on visual surveillance, human movement analysis, and advanced computer vision systems such as the Keck Laboratory for the Analysis of Visual Movement. Established in 1998, the Keck Lab uses a 64-camera array to study 3D human motion tracking and shape recognition. His work spans projects like codebook-based background subtraction for surveillance and clothing appearance models for persistent tracking. He leads interdisciplinary research on laser beam propagation through atmospheric turbulence and has secured significant grants, including a $4M Multidisciplinary Research Initiative contract. His recent publications emphasize AI-driven solutions for media forensics, generative models, and adversarial attacks on vision systems. Research contributions include innovations in neural rendering (FlexNeRF), personalized clothing compatibility frameworks, and systems for detecting deepfakes and video tampering. His work bridges theoretical advancements with real-world applications in security, healthcare, and retail technology.