Prof. Marc Stamminger is a Professor of Visual Computing at FAU since 2002, leading the Chair of Computer Science 9 (Computer Graphics). His work focuses on algorithms for synthesizing and analyzing images through 3D modeling, LiDAR/Radar capture, and light simulation. He co-leads FAU Solar, applying 3D modeling for environmental lighting analysis under varying conditions. Stamminger has published over 250 papers, winning prestigious awards like the Siggraph Test-of-Time Award. He holds executive roles in Eurographics and is Vice Dean of FAU's Technical Faculty. Research interests span neural rendering , 3D reconstruction , radar imaging , and medical visualization . Recent work emphasizes radiance field rendering (e.g., VR-Splatting, INPC) and radar-based human motion tracking. His lab's FAU Solar project integrates large-scale 3D models with environmental lighting simulations. Publications trends highlight neural rendering optimizations , radar-MIMO systems , and agricultural digital twins . Key collaborations involve medical imaging (e.g., vocal fold reconstruction) and autonomous driving data generation. Awards: Siggraph Test-of-Time (2023?), 2× Siggraph Best-Of-Show Grants/Teams: FAU Solar Lab, Eurographics leadership, FAU Vice Dean Labs: Chair of Computer Science 9, FAU Solar Initiative
Alla Sheffer is a Professor and Associate Head of Faculty Affairs in the Department of Computer Science at the University of British Columbia, Faculty of Science. She is affiliated with multiple research centers including CAIDA (Centre for Artificial Intelligence Decision-making and Action), the Institute of Applied Mathematics, and ICICS (Institute for Computing, Information and Cognitive Systems). B.Sc., Hebrew University, Jerusalem (1991) M.Sc., Hebrew University, Jerusalem (1995) Ph.D., Hebrew University, Jerusalem (1999) Postdoctoral Research Associate, University of Illinois, Urbana-Champaign (1999-2001) Assistant Professor, Technion, Israel (2001-2003) Assistant Professor, University of British Columbia (2003-2008) Associate Professor, University of British Columbia (2008-present) Professor Sheffer's research focuses on geometry processing, addressing algorithmic challenges in digital shape modeling and manipulation. Her work primarily deals with discrete geometry representations, specifically meshes (polygonal model representations), with applications in computer graphics and computer-aided engineering. She utilizes tools from computational and differential geometry, discrete mathematics, and graph theory to generate, manipulate, and edit discrete geometric models. Her research spans virtual and augmented reality, visual computing, and 3D modeling, with significant contributions to sketch-based modeling, mesh processing, and cloth simulation. The 15 most recent publications reveal a consistent research trajectory in geometry processing, with recent work focusing on vector sketch processing, VR drawing tools, and advanced mesh manipulation techniques. Her work demonstrates a strong connection between human perception and computational methods, particularly in the interpretation of freehand sketches and the generation of perceptually-accurate geometric representations. The recurring themes across her publications include flowlines, curve networks, mesh parameterization, and the application of perceptual studies to improve algorithmic outputs. Eurographics Fellow ACM Fellow IEEE Fellow Royal Society of Canada Fellow SIGGRAPH Academy Member UBC Killam Research Prize NSERC Discovery Accelerator Supplement IBM Faculty Award Professor Sheffer has supervised numerous doctoral and master's students, with recent theses focusing on geometric mesh processing, vector sketch interpretation, VR drawing tools, and garment modeling. Her research group maintains strong connections with industry through various partnerships and has received substantial grant funding to support their innovative work in geometry processing and computer graphics. She teaches courses in computer graphics, geometric modeling, and video game programming, contributing significantly to both undergraduate and graduate education in computer science.
Sezer Karaoglu is a Lecturer and part-time postdoctoral researcher at the Computer Vision Group, Informatics Institute, University of Amsterdam. He is also the CTO and Co-Founder of 3DUniversum, a technology spin-off of the University of Amsterdam that provides state-of-the-art 2D/3D computer vision solutions. Additionally, he has co-founded other startups including Scanm and 3DHealthScan. Dr. Karaoglu received his PhD from the Computer Vision Group, Informatics Institute, University of Amsterdam, with research funded by the COMMIT project. His educational background includes a double master's degree: an optics, image and vision master's degree from University Jean Monnet in France and a media technology master's degree from Gjovik University College in Norway. He completed his undergraduate studies with honors at Istanbul Technical University in Telecommunication Engineering. His research focuses on Artificial Intelligence and 3D Computer Vision, with specific interests in SLAM, re-localization, 3D reconstruction, 3D object detection and segmentation, synthetic media, generative AI, deep fake creation and detection, and VR/AR technologies. His work has significant applications in healthcare, particularly in using deepfake technology for therapy for victims of sexual violence-related PTSD and moral injury, as documented in a Frontiers in Psychiatry article. Analyzing his recent publications reveals a strong trend toward neural scene reconstruction, intrinsic image decomposition, and the application of diffusion models to computer vision problems. His research increasingly integrates 3D scene understanding with language models, as evidenced by his work on language-to-3D scene generation. The applications span from healthcare (deeptherapy.ai) to media authenticity (deepfake detection) and industrial applications. ICT.OPEN Poster Award (3rd Position), Oct'13 Pascal VOC'12 Classification challenge, 2nd Position, Sep'12 Pascal VOC'12 Detection challenge, 3rd Position, Sep'12 Best project award at Nokia and CIMET project competition Outstanding reviewer at CVPR'21 PROVADA Future Startup Battle winner Best Dutch AI startup by Valuer Dr. Karaoglu has supervised numerous PhD, Master's, and Bachelor's students, demonstrating his commitment to academic mentorship. His research has attracted significant media attention, with features on Dutch national TV programs including NPO, VPRO, RTL, and international outlets like BBC News. He has received research funding through the COMMIT project during his PhD studies and has successfully translated his research into commercial applications through his startups. His work on deepfake technology has been applied in innovative therapeutic contexts through DeepTherapy.ai, showing the real-world impact of his research. Dr. Karaoglu leads research efforts at the Computer Vision Group Amsterdam and through his company 3DUniversum, which has developed applications like weScan, DeepTherapy, and FairFake.ai. His team collaborates with various institutions including the Netherlands Film Academy for grief therapy applications using deepfake technology. The DeepTherapy project represents a particularly impactful application of his work, using deepfake technology to help victims of sexual violence confront perpetrators in therapeutic settings.
Iliyan Georgiev is a research scientist at Adobe, specializing in advanced computer graphics and physically based rendering. He holds a Bachelor's degree in Computer Science from Sofia University, Bulgaria, and a Master's degree from Saarland University, Germany, supported by a fellowship from the Max-Planck Institute. His work focuses on improving rendering efficiency through Monte Carlo methods, light transport simulation, and neural rendering techniques. Georgiev's research bridges the gap between theoretical and applied graphics, with contributions to bidirectional rendering algorithms, importance sampling, and 3D scene modeling. His publications highlight innovations in variance reduction, path sampling, and material-aware rendering. He has collaborated with leading institutions and companies, including Intel Visual Computing Institute, Disney Research Zürich, Weta Digital, Chaos Group, and Autodesk. Notable scientific awards include the Best Student Paper Award at ICPRAM 2025 and the Best Paper Award at EGSR 2024.
Dr. Luiz Felipe Aguinsky is a Lecturer in Computational Nanoelectronics and Deputy Group Leader of the DeepNano Research Group at the University of Glasgow. He holds a PhD (Dr. techn.) from TU Wien, Austria, where he specialized in semiconductor fabrication process modeling. As an Erwin Schrödinger Fellow at ETH Zurich, he developed machine learning-enhanced models for memristors. His research focuses on computational nanoelectronics, combining advanced simulation techniques with cutting-edge materials science. Education: PhD (Dr. techn.) in Microelectronics, TU Wien (Austria), 2019 (with distinction) Erwin Schrödinger Fellowship at ETH Zurich's Computational Electronics Group (2021–2023) Research Interests: His work integrates machine learning with atomistic simulations to address challenges in semiconductor manufacturing. Key areas include: High-performance TCAD for nanofabrication processes Quantum transport and neuromorphic computing Applied computer graphics for nonimaging applications Level-set methods for surface evolution modeling Publications Trends: Recent work emphasizes knudsen diffusion modeling for nanofabrication, atomic layer deposition simulations, and plasma etching optimization. Cross-disciplinary methods like ray tracing and machine learning feature prominently in his latest projects. Awards & Fellowships: EUROSOI-ULIS Best Poster Award (2021) Erwin Schrödinger Fellowship (FWF, 2023–2025) Professional Activities: Active member of IEEE Nanotechnology Council's Modelling & Simulation Technical Committee. Co-author of over 15 peer-reviewed publications since 2019, with contributions to IEEE NANO, SISPAD, and EuroSOI conferences. Labs/Teams: Leads computational modeling efforts in the DeepNano Research Group, collaborating globally on TCAD innovations for next-generation semiconductor devices.
Martin Magnusson is a Professor at the Department of Natural Sciences and Technology, Örebro University, leading the Center for Applied Autonomous Sensor Systems (AASS) and the Robot Navigation and Perception Lab . His research focuses on robotics and artificial intelligence , particularly 3D mapping, localization, radar-based navigation, and human-robot interaction . Email: martin.magnusson@oru.se Phone: +46 19 303870 Location: Room T1222 His work addresses fundamental challenges in achieving robust autonomy through innovations like the 3D Normal Distributions Transform (3D-NDT) and methods for scan registration in dynamic environments. Recent research extends to radar-based navigation and heterogeneous map data integration , with ethical implications regarding military applications of autonomous systems. Key research themes include: Autonomous Perception: Radar and lidar sensor fusion for localization Dynamic Mapping: Flow-aware and quality-assessed environmental models Human-Aware Robotics: Predictive modeling for safe shared-space navigation Professor Magnusson teaches Computer Graphics , connecting academic principles (e.g., ray tracing, light scattering) to applied research in radar simulation models and neural rendering . His research projects span DARKO (agile production robots), NiCE (changing environment navigation), and Radarize (underground autonomous vehicles).
Dr. Steffen Frey is an Assistant Professor in the Scientific Visualization and Computer Graphics group within the Bernoulli Institute at the University of Groningen's Faculty of Science and Engineering. He also maintains an affiliation with the Faculty of Medical Sciences/UMCG in the Robotics and image-guided minimally-invasive surgery (ROBOTICS) research group. His work bridges computer science with practical applications in medical and geoscientific domains. His research interests focus on scientific visualization, computer graphics, and interactive visualization techniques. Dr. Frey specializes in developing novel methods for flow estimation, temporal interpolation, parameter sensitivity analysis, and visualization of complex scientific data, particularly in porous media and fluid dynamics. His work often involves creating scalable solutions for big data visualization problems and applying visualization techniques to medical applications such as bone cement simulation. Analysis of his recent publications reveals a strong focus on machine learning approaches to scientific visualization, particularly in temporal interpolation and ensemble data analysis. His work combines traditional computer graphics techniques with modern deep learning methods to solve challenging visualization problems in scientific domains. The research demonstrates increasing sophistication in handling complex multi-dimensional datasets while maintaining interactive performance. 2019 IEEE Scientific Visualization Contest Winner Dr. Frey actively collaborates with researchers internationally, as evidenced by his co-authorship with scientists from various institutions worldwide. His work contributes to multiple Sustainable Development Goals, particularly those related to clean water and sanitation through his porous media flow research. He has supervised multiple students through research projects and thesis work, though specific names are not listed in the provided materials.
Prof. Piotr Białas is a Professor of Physical Sciences and Director of the Institute of Applied Informatics at Jagiellonian University. He holds a habilitation in physics from the same institution and has served as department head and faculty member since 1993. His research focuses on GPU programming, multi-core processor optimization, and theoretical physics areas like simplicial gravity and quantum chromodynamics on networks. He has supervised over three doctoral and dozens of master's theses. Current projects include GPU acceleration for medical imaging (J-PET tomograph) and real-time FPGA-based data processing. Education: PhD in Physics (1993), MSc in Physics (1990) from Jagiellonian University. Academic roles include membership in the Academic Council of Technical Informatics and Complex Systems Commission at Polish Academy of Arts and Sciences. Invited professorships at universities in Amsterdam, Bielefeld, Barcelona, and Saclay. Specializes in CUDA optimization, parallel computing, and medical imaging algorithms.
Miriah Meyer is a Professor in the Department of Science and Technology (ITN) at Linköping University, supported by the Wallenberg Autonomous Systems Program (WASP). Her research focuses on designing visualization tools to enhance data analysis and understanding through interdisciplinary approaches integrating computer science, design, social science, and humanities. Previously, she held positions as an Associate Professor at the University of Utah’s School of Computing and completed a postdoctoral fellowship at Harvard University. Education: Bachelor’s in Astronomy and Astrophysics, Penn State University PhD in Computer Science, University of Utah Postdoctoral Fellowship in Visualization, Harvard University Research Interests: Meyer’s work emphasizes human-centered design of visualization systems to address societal challenges. Key areas include: Exploratory and reflective data analysis Interdisciplinary methodologies Design studies in visualization Impact of technology on societal perceptions Publications: Her recent work explores feminist theory in visualization (2025), preregistration in research design (2024), and socio-technical transitions in dashboarding (2024). She advocates for rigorous, ethical practices in visualization design. Awards: Recognitions include TED Fellow (2013), MIT TR35 (2012), and Microsoft Research Faculty Fellowship (2011). Labs & Teams: Active in the Visualization and Interaction Design Group at LiU and former contributions to the Scientific Computing & Imaging Institute (SCI) at the University of Utah.
Prof. Dr. Fabian DI FIORE is a Lecturer and Research Coordinator at the Department of Computer Science, Faculty of Sciences, Hasselt University. He is affiliated with the Expertise Center for Digital Media (EDM) and leads research in Computer Graphics, Virtual Reality, and Extended Reality (XR). His roles include coordinating research projects and teaching courses such as Operating Systems, Computer Animation & Simulation, and Computer Graphics & Visual Computing. His research focuses on modeling and simulation, computer vision, and digital media applications. Notable projects include XR innovations for manufacturing, digital support for industrial processes, and collaborative virtual environments for education. He coordinates 16 active research projects, emphasizing XR infrastructure and applied technologies in industry and healthcare. Prof. DI FIORE supervises PhD candidates in Extended Reality applications, such as Psychomotor Task Assistance and Training using XR. He is involved in education initiatives like the International interdisciplinary project and the International School program. His work bridges academic research and practical applications, with a focus on innovation in digital media and educational technology. His teaching responsibilities include coordinating courses on operating systems, computer animation, and project management. He is a co-owner of key training components such as Computer Architecture and International interdisciplinary projects, reflecting his dual role in education and research leadership.
University of Applied Sciences and Arts LucerneSwitzerland
Ron Porath is a Lecturer at the Lucerne School of Computer Science and Information Technology (HSLU), specializing in Cybersecurity and Computer Graphics. He holds a Dr. Rer. Nat. from TU Kaiserslautern (2002) and a Dipl. Phys. from ETH Zurich (1998). His academic career includes roles as Deputy Program Director for the BSc Cyber and Information Security program (2024–present) and Tech Project Manager at UBS (2016–2023). Education: Dr. Rer. Nat., TU Kaiserslautern (2002) – Elektronendynamik und Nanotechnologie Dipl. Phys., ETH Zürich (1998) – Theoretical Physics Key Research Areas: Information Security, 2D/3D Computer Graphics, Data Security in Visual Computing, Number Theory Academic Memberships: Eurographics (2022), European Physical Society (2002), Swiss Physical Society (2002) His teaching focuses on Crises Recovery Strategies (CRS) , Data Leakage Prevention (DLP) , and Kryptologie & Anwendungen . Notable publications include books on cybersecurity (Springer Vieweg, 2020) and metaverse-related research. He has been recognized with the 'True Innovator' award three times (2021) for cross-disciplinary contributions. Professional experience spans banking, academia, and research, including roles at Credit Suisse (2004–2011) and Pragmatica (2011–2016). Active in both theoretical physics (plasmon dynamics, semiconductor physics) and applied computer science (ray tracing, metaverse technologies).
Tor Aamodt is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia within the Faculty of Applied Science. He has been a faculty member at UBC since 2006 and maintains an active research program in computer architecture with a focus on GPU systems. His academic journey includes a BASc, MASc, and PhD from the University of Toronto, followed by industry experience at NVIDIA where he worked on the memory system architecture of the GeForce 8 Series GPU. Professor Aamodt's research spans computer architecture with particular expertise in accelerators for deep neural networks and graphics processor unit architecture for non-graphics computing. His work has evolved from foundational GPU architecture research to cutting-edge applications in ray tracing, robotics acceleration, and energy-efficient computing. He has made significant contributions to understanding GPU memory systems, interconnect architectures, and the application of GPUs to machine learning workloads. His research group has developed influential tools including the first widely used GPGPU architecture simulator and the Vulkan-Sim ray tracing simulator. His recent publications reveal a strong trend toward real-time ray tracing acceleration and robotics applications, with substantial work on optimizing tree traversal algorithms for ray tracing workloads. The research shows a clear evolution from general GPU architecture studies to specialized hardware-software co-design for specific application domains, particularly in rendering and robotics. His group consistently publishes at top-tier architecture venues including MICRO, ISCA, and ASPLOS. IEEE Micro Top Picks (3 papers) Communications of the ACM Research Highlight MICRO Conference Hall of Fame NVIDIA Academic Partnership Award (2010) NSERC Discovery Accelerator (2016-2019) Google Faculty Research Award (2016) SAMSUNG Global Research Outreach Award (2023) IISWC 2023 Best Paper Award Professor Aamodt has advised numerous graduate students who have gone on to positions at leading technology companies including Google. His research has been supported by major grants from NSERC, NVIDIA, Google, and Samsung. He has served in leadership roles including Program Chair for ISPASS 2013 and General Chair for ISPASS 2014, and was a Visiting Associate Professor at Stanford University during his 2012-2013 sabbatical. His group maintains active collaborations with industry partners and has produced influential open-source tools including GPGPU-Sim and Vulkan-Sim.
Rhenish Friedrich Wilhelm University of BonnGermany
Prof. Dr. Carsten Burstedde is a faculty member at the Institut für Numerische Simulation within the University of Bonn , specifically affiliated with the Faculty of Mathematics and Natural Sciences . His work focuses on developing scalable algorithms for adaptive mesh refinement (AMR) that operate efficiently on the world’s largest supercomputers. He leads the development of the p4est software library , a foundational tool for parallel AMR applications, and contributes to projects like ForestClaw for simulating volcanic ash transport in atmospheric flows. His research spans scientific computing , applied mathematics , and high-performance computing . Key application areas include geophysics (mantle convection, seismic wave propagation), fluid dynamics (incompressible flows, volcanic ash transport), and uncertainty quantification for inverse problems. He emphasizes non-conforming mesh techniques and parallel numerical solutions of PDEs , with a particular interest in hybrid mesh algorithms for complex domains. The 15 most recent publications highlight his expertise in adaptive mesh refinement across diverse contexts: 2021 works on heterogeneous systems and ghost layer optimization , 2020 contributions to p4est software and CPU ray tracing of AMR data, 2019 studies on Morton-type space-filling curves , and 2018–2016 projects enhancing ParFlow and ESPResSo with adaptive methods. Earlier papers (2015–2012) address Bayesian inverse problems , level-set methods , and multi-scale geodynamics . Scientific Awards include the Springer CSE Prize (2011) and the NSF TeraGrid Capability Computing Challenge (2008) . He has advised PhD student Johannes Holke , with whom he developed tetrahedral space-filling curves and hybrid AMR algorithms . His teaching includes courses on scientific computing , adaptive mesh refinement , and mathematics in music . The p4est summer school (2020) and collaboration with Donna Calhoun (ForestClaw project) underscore his leadership in computational science outreach and education.
Toshiya Hachisuka is an Associate Professor in the Department of Computer Science at the University of Waterloo, part of the School of Computer Science. His research focuses on combining applied mathematics, computer science, and physics to address challenges in visual simulation, particularly in computer graphics, light transport, and computational statistics. He holds a Ph.D. from the University of California, San Diego (2011) and a B.Eng. from the University of Tokyo (2006). Research Interests: Hachisuka’s work spans light transport simulation , Monte Carlo rendering , numerical analysis , and fluid dynamics . He develops algorithms for efficient rendering and simulation, including methods like segment-based light transport and quantum ray marching. His techniques often integrate mathematical rigor with computational efficiency. Publications: His recent work explores advancements in Monte Carlo methods, fluid simulation, and quantum computing applications in rendering. Notable themes include denoising techniques , boundary element methods , and gradient-domain rendering . Awards: No scientific awards explicitly mentioned in the text. Advising & Grants: No specific students or grants listed, but his extensive publication record suggests active research collaboration. Labs/Teams: Involved in computer graphics research groups at the University of Waterloo, contributing to cutting-edge rendering and simulation projects.
Jacco Bikker is a Senior Lecturer at the Academy for AI, Games & Media at Breda University of Applied Sciences, where he founded the CMGT program (formerly known as IGAD) in 2006 together with Frank Peters. With a background in the Dutch game industry as a rendering specialist, he brings practical industry experience to his academic role. Dr. Bikker defended his doctoral thesis on Ray Tracing in Real-time Games in 2012 at Delft Technical University under the supervision of Professor Erik Jansen. His research focuses on cutting-edge graphics techniques including real-time ray tracing on CPU and GPU, path tracing for real-time global illumination, denoising, and artificial intelligence applications for rendering challenges. His work bridges the gap between academic research and industry implementation, with strong emphasis on knowledge transfer to students and practitioners. His research output shows a clear progression from foundational rendering techniques to advanced real-time ray tracing implementations. Early work focused on path guiding and BRDF matching algorithms, while more recent contributions center on practical implementations of real-time ray tracing systems. His research spans both theoretical computer graphics and practical software optimization challenges faced in game development. As an active member of the graphics community, Bikker serves in leadership roles including as Paper Chair for High Performance Graphics (HPG) '24 and as Chair for ACM/Eurographics committees. He regularly presents at industry events and has contributed to press discussions about game development education and technology. Dr. Bikker is the creator of the TinyBVH open-source library, a single-header dependency-free BVH construction and traversal library that has gained significant traction in the graphics community. The library is used by projects including EA SEED's Gigi and Unity implementations, demonstrating its practical impact on real-world graphics applications.
