جست‌وجوی استاد و پژوهشگر

Markus Steinbergerمشاهده پروفایل

دانشیار

• GPU Computing
• Computer Graphics
• Parallel Processing
• +۳ مورد دیگر

Markus Steinberger is an Associate Professor at Graz University of Technology (Austria), leading the GPU Computing and Visualization Group at the Institute for Computer Graphics and Vision. He holds an MSc and PhD in Computer Science from TU Graz, with a postdoc and multiple leadership roles in academic and industry labs, including NVIDIA and the Max Planck Institute. His research focuses on GPU scheduling, parallel computing, and high-performance visualization techniques. He has led teams at TU Graz, Huawei Technologies (Cloud Rendering Lab), and the Max-Planck-Center for Visual Computing. Education 11/2020: Habilitation in Practical Computer Science at TU Graz 10/2013: PhD in Computer Science (Dynamic Resource Scheduling on Graphics Processors) 10/2010: MSc in Telematics 10/2005: BSc in Telematics Research Interests Steinberger’s work centers on optimizing GPU computing for real-time rendering and parallel processing. He explores efficient resource scheduling, dynamic graph management, and high-performance visualization techniques, with applications in cloud rendering, scientific visualization, and interactive graphics. His methods emphasize scalability and real-world applicability in both academic and industrial settings. Awards Heinz Zemanek Prize (2016) – First Austrian recipient GI Dissertation Prize (2014) – Best dissertation in German-speaking computer science Multiple Eurographics Best Paper Awards (2021, 2020, 2014) HPEC Best Student Paper (2017) ACM CHI Honorable Mention (2014) Advising & Grants Steinberger has advised numerous students and led projects funded by EU initiatives and industry partnerships. His research has been recognized through grants supporting GPU scheduling, cloud rendering, and parallel computing. Labs & Teams Leads the GPU Computing and Visualization Group at TU Graz and directed the Cloud Rendering Lab at Huawei, focusing on scalable rendering solutions for distributed systems.

• Model-Driven Engineering
• AutomationML
• Cyber-Physical Systems (CPS)
• +۵ مورد دیگر

Manuel Wimmer is a Professor affiliated with the Department of Business Informatics at TU Wien's Faculty of Informatics. His main research area is Model-Driven Engineering , focusing on topics such as AutomationML, Cyber-Physical Systems (CPS), and industrial standards like IEC 62264 and ISA-95. He leads the Network Lab and contributes to interdisciplinary projects involving robotics, cloud computing, and blockchain applications. Research Interests: Model Transformation, Tool Interoperability, Industrial Automation, Educational Methodologies in Software Engineering. Key Technologies: UML, ATL, OPC UA, AutomationQL. Recent work emphasizes bridging metamodeling platforms (e.g., ADOxx/EMF integration) and adapting robotic mission planning systems. He has published extensively in workshops like MDE 2023 and conferences on model-driven engineering. Teaching activities include remote-learning strategies for software engineering education, as documented in his 2021 paper. No explicit awards are listed, but his contributions to standards like AutomationML reflect industry recognition.

Thomas Eiterمشاهده پروفایل

استاد

• Answer Set Programming
• Knowledge Representation
• Logic Programming
• +۷ مورد دیگر

Thomas Eiter is a Professor at TU Wien's Institute of Logic and Computation. His research focuses on declarative programming paradigms, knowledge representation, and artificial intelligence. He leads projects in neurosymbolic systems, answer set programming (ASP), and stream reasoning, with applications in visual question answering, scheduling optimization, and semantic scene generation. Eiter has contributed to foundational work in ASP semantics, computational complexity, and hybrid reasoning frameworks. His work bridges logical formalisms with practical AI challenges, emphasizing explainability and scalability. Projects like ALASPO and neurosymbolic integration showcase his focus on advancing both theoretical and applied aspects of AI. Projects: HumanE AI Network, WASP, REWERSE Research Themes: Neurosymbolic AI, Answer Set Programming, Stream Reasoning Notable achievements include pioneering work on semiring-based reasoning frameworks and developing efficient ASP solvers like Alpha. His contributions span over 471 publications, emphasizing interdisciplinary applications in computer vision, robotics, and automated planning.

Yingying (Samara) Renمشاهده پروفایل

استادیار

• Digital Fabrication
• Physics-Based Simulation
• Inverse Design Optimization
• +۳ مورد دیگر

Yingying (Samara) Ren is an Assistant Professor in Computer Science at the Institute of Science and Technology Austria (ISTA), leading the Geometric Computing and Digital Fabrication group. Her research focuses on digital fabrication, physics-based simulation, and computational inverse design, with applications in medical devices, architecture, and soft robotics. She holds a PhD from EPFL (2019–2024) and dual BS degrees in Mathematics and Computer Science from UIUC (2015–2019). Her work explores novel structures and materials through geometric reasoning and numerical methods. Notable projects include Tensors (tensegrity structures with elastic rods), C-shells (deployable gridshells), and Umbrella Meshes (freeform deployable mechanisms). Recent contributions span inflatable structures, elastic knots, and weaving-based architectural systems. Ren’s research integrates computational design, material science, and advanced manufacturing. She has published in top venues like ACM Transactions on Graphics and SIGGRAPH, focusing on deployable systems, elastic mechanics, and inverse design. Her lab emphasizes practical fabrication, with prototypes ranging from small-scale elastic knots to large architectural pavilions.

Manas Bhargavaمشاهده پروفایل

پژوهشگر

• Soft robotics
• Deformable structures
• Computational design
• +۵ مورد دیگر

Manas Bhargava is a Postdoctoral Researcher at the Institute of Science and Technology Austria, working in the Material Molli Lab under Prof. Jérémie Palacci. Previously, he completed his PhD with Prof. Bernd Bickel, focusing on the design and control of deformable structures. His research spans several cutting-edge domains in computational design and robotics. Bhargava's work integrates principles from computer graphics, mechanical engineering, and materials science to create innovative deformable structures. His projects range from building 3D lighting displays using folded PCBs to developing musculoskeletal soft robots with laser-controlled artificial muscles. He has presented his research at prestigious venues including SIGGRAPH, Eurographics, and the Think and Drink Conference at ISTA. Bhargava has published in top-tier venues including ACM Transactions on Graphics (SIGGRAPH) and Computer Graphics Forum. His work demonstrates a strong trend toward practical computational fabrication methods that bridge digital design with physical implementation, particularly in soft robotics and interactive displays. The research shows increasing sophistication in control mechanisms and material integration across his publications. As an academic mentor, Bhargava has supervised multiple students including Chris Wernke (bachelor thesis on Dynamic Simulation and Fabrication of Origami Robots) and Yuhan Zhang (master thesis on Compatible Triangulations for Fabricating Deformable Structures). His collaborative approach is evident in co-supervision arrangements and multi-institutional projects spanning ETH Zurich and ISTA.

Haisen Zhaoمشاهده پروفایل

استاد

• Computer Graphics
• Digital Fabrication
• Additive Manufacturing
• +۵ مورد دیگر

Haisen Zhao is a Professor at Shandong University (SDU), affiliated with the School of Computer Science and Technology and the Interdisciplinary Research Center. His research focuses on geometric processing and digital fabrication, including additive and subtractive manufacturing. He completed his PhD at SDU in 2018 under Baoquan Chen, followed by postdoctoral research at the University of Washington (with Adriana Schulz) and IST Austria (with Bernd Bickel). He has authored over 20 top-tier publications in venues like ACM SIGGRAPH/Asia and IEEE TVCG, and holds multiple patents. Education: PhD in Computer Science (2018, SDU), Master’s (2014, SDU), and Bachelor’s (2011, SDU). Key awards include the CCF Doctoral Dissertation Award (2019) and Shandong Natural Science Award (2020). He leads a research group focused on advanced manufacturing techniques, advising PhD and Master’s students in areas like robotics, computer-aided design, and fabrication optimization. Teaching responsibilities include courses on computer graphics, human-computer interaction, and advanced topics for both undergraduates and graduates. His lab actively explores hybrid manufacturing strategies, inverse design methods, and robotic fabrication systems. Recent projects include neural accessibility learning for CNC machining and generative design for microstructure fabrication.

Tomáš Skřivanمشاهده پروفایل

پژوهشگر ارشد

• Physics Simulation
• Computer Graphics
• Numerical Methods
• +۳ مورد دیگر

Tomáš Skřivan serves as a Research Fellow at the Hoskinson Center for Formal Mathematics , Carnegie Mellon University. His work bridges formal mathematics with practical scientific computing through the development of the SciLean library in Lean 4, targeting enhanced reliability in machine learning and simulation software. Skřivan's research spans interdisciplinary domains with core emphases on: Physics-based simulation of fluid dynamics and wave phenomena Computer graphics algorithms for light transport and rendering Formal verification techniques applied to numerical methods Mathematical modeling of viscoelastic materials His publication trajectory since 2016 reveals evolving expertise from computational fluid dynamics (water wave simulation, viscoelastic modeling) toward formal methods in scientific computing, consistently merging theoretical rigor with practical implementation. Recent work on SciLean represents a strategic pivot toward verified software foundations. As a key contributor to the Hoskinson Center's mission, Skřivan collaborates on projects leveraging proof assistants to eliminate errors in scientific code. The center, established through Charles Hoskinson's support, pioneers mathematically guaranteed correctness in computational science through formal verification frameworks.

Thomas Auzingerمشاهده پروفایل

پژوهشگر ارشد

• Computational Design
• Visual Computing
• Medical Visualization
• +۳ مورد دیگر

Thomas Auzinger is a Research Fellow and head of the AutoMold spin-off project at the Institute of Science and Technology Austria (ISTA). He previously held a postdoctoral position in Computational Fabrication under Prof. Bernd Bickel at ISTA. His educational background includes B.Sc. and M.Sc. degrees in Mathematical Physics from the University of Vienna and a PhD in Computer Graphics from TU Wien. He also completed entrepreneurial training through the I.E.C.T. Summer School and the Ludwig Boltzmann Society's Innovator’s Road Program. His research focuses on computational design for fabrication, particularly in mechanical and optical applications, as well as visual computing topics like anti-aliasing and medical visualization. He leads business development for AutoMold, aiming to commercialize automated mold design in industrial tooling. He has published in top-tier journals and contributed to conferences as a Program Committee Member (Pacific Graphics 2016, Eurographics 2020 Short Paper track) and co-organizer (Symposium on Computational Fabrication 2016). Auzinger has taught courses on rendering, visualization, and GPU programming at TU Wien and ISTA, and delivered invited courses on computational fabrication internationally. His work bridges academic research and industry application, emphasizing innovation in fabrication and visual computing.

Ruslan Guseinovمشاهده پروفایل

پژوهشگر ارشد

• Computational Design
• Computer Graphics
• Digital Fabrication
• +۳ مورد دیگر

Ruslan Guseinov is a computational design researcher specializing in digital fabrication of curved structures and programmable matter, affiliated with IST Austria where he completed his PhD in 2020 under Bernd Bickel's supervision. His educational background includes: PhD in Computer Science, IST Austria, 2020 Guseinov's research bridges computer graphics, geometry processing, and materials engineering to develop algorithms for manufacturing complex shapes from flat materials. His work enables cost-effective glass façade design and self-actuating structures through computational geometry innovations, with applications in architecture and soft robotics. Key contributions include tension-actuated curvature methods and temporal morphing programming for programmable matter. His publication portfolio demonstrates consistent focus on computational fabrication techniques, evolving from foundational CurveUps research (2017) to advanced applications in glass engineering and programmable matter (2020), reflecting interdisciplinary collaboration across computer science, robotics, and architectural design. He has received significant recognition: Eurographics Best PhD Thesis 2021 TWIST Fellowship 2020 SIGGRAPH PhD Thesis Fast Forward 2020 No formal advising relationships or research grants are documented in available sources. His media coverage spans major outlets including ScienceDaily, phys.org, and Le Monde, highlighting real-world impact in industrial manufacturing. Guseinov operated within Bernd Bickel's research group at IST Austria, focusing on computational design and fabrication methodologies that transform theoretical concepts into practical manufacturing solutions.

Daniel Cornelمشاهده پروفایل

پژوهشگر

• Flood Modeling
• Hydrology
• Computational Fluid Dynamics
• +۳ مورد دیگر

Daniel Cornel is a researcher affiliated with TU Wien's Department of Engineering Hydrology, part of the E222-02 research group. He holds a Dipl.-Ing. (engineering diploma) and a Dr.techn. (technical doctorate). His work focuses on integrating computational methods with environmental hydrology, emphasizing flood modeling, high-performance computing, and geospatial visualization. Cornel collaborates extensively with experts like Prof. Günter Blöschl and Prof. Jürgen Waser on projects such as the HORA 3.0 flood risk zoning initiative. His research interests span GPU-accelerated flood simulations, hydrodynamic modeling at regional scales, and decision-support systems for disaster management. Notable contributions include developing interactive visualization tools for real-time flood data and VR-based training modules for emergency response. Cornel also explores algorithm optimization for terrain modeling and subsurface network visualization. Key projects include the 'Integrated Simulation and Visualization for Flood Management' framework and the 'Master of Disaster' VR training system. His work bridges computational science with environmental engineering, addressing both technical challenges and practical applications in flood risk mitigation.

Friedrich Fraundorferمشاهده پروفایل

استاد

• 3D Computer Vision
• Robot Vision
• Multi View Geometry
• +۴ مورد دیگر

Friedrich Fraundorfer is a Professor at Graz University of Technology, specializing in 3D Computer Vision and Autonomous Systems at the Institute of Computer Graphics and Vision (ICG). He has held academic positions at institutions including ETH Zurich, University of North Carolina at Chapel Hill, and Technische Universität München, where he served as Deputy Director of the Chair of Remote Sensing Technology. Research : Focuses on Micro Aerial Vehicle (MAV) autonomy, Visual-Inertial Fusion, and Multi-View Geometry. Projects : Led EU-funded SFly (autonomous MAVs for search-and-rescue), SNF MAV (camera-only 3D mapping), and VCharge (vision-based self-driving cars). Teaching : Offers courses like 'Camera Drones' and 'Mathematical Principles in Vision.' His Pixhawk project created open-source MAV platforms adopted globally. Key Collaborations : With NVIDIA, Volkswagen AG, University of Zurich, and German Space and Aerospace Center (DLR). His students (e.g., Dominik Hirner, Rafael Weilharter) have published on lightweight CNNs for stereo vision and self-supervised 3D reconstruction.

Emanuele Rodolàمشاهده پروفایل

استاد

• Machine Learning
• Geometry Processing
• Computer Vision
• +۱ مورد دیگر

Emanuele Rodolà is a Full Professor of Computer Science at Sapienza University of Rome , leading the GLADIA group (Geometry, Learning and Applied AI) funded by an ERC Grant and a Google Research Award. Former Assistant (2017-2020) and Associate Professor at Sapienza Postdoc at USI Lugano (2016-2017), TU Munich (Alexander von Humboldt Fellow, 2013-2016), and University of Tokyo (JSPS Research Fellow, 2013) His research spans geometry processing , graph/geometric deep learning , computer vision , and language/sound processing , with over 100 publications. He has served on program/organizing committees of top conferences and founded successful workshops in machine learning and graphics. Ellis Fellow ERC Grant recipient Google Research Award Alexander von Humboldt Fellow JSPS Research Fellow

Linus Frankeمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Perceptual Rendering
• Computer Vision
• +۳ مورد دیگر

Linus Franke is a postdoctoral researcher at Inria Sophia Antipolis in France, affiliated with the GraphDeco research group under George Drettakis. He previously completed his PhD at the Chair of Visual Computing , Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) in Germany under Marc Stamminger. His research focuses on Computer graphics Perceptual rendering Computer vision Machine learning Neural rendering Novel view synthesis Key trends in his recent publications include neural rendering , 3D Gaussian splatting , radiance fields , and real-time rendering with applications in virtual reality and light field displays. His work often integrates point clouds , differentiable rendering , and GPU optimization techniques. His personal website at lfranke.github.io highlights projects like VET (Visual Error Tomography) and TRIPS (Trilinear Point Splatting for Real-Time Rendering).

Simon LUCASمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Real-Time Rendering
• Appearance Modeling
• +۵ مورد دیگر

Simon LUCAS is a Postdoctoral Researcher in computer graphics at Inria Sophia-Antipolis, affiliated with the GraphDeco research team. His work focuses on light transport and appearance modeling for real-time rendering applications. Research Interests Light transport simulation and optimization Material appearance modeling Real-time rendering techniques Procedural texture generation Modeling of complex surface materials Academic Background Master's degree research on procedural texture generation and glinty materials PhD studies centered on porous materials appearance modeling Current Work Developing novel rendering algorithms at GraphDeco team Investigating appearance modeling for computer graphics applications

• Cognitive Neuroscience
• Electroencephalography (EEG)
• Biosignal Processing
• +۶ مورد دیگر

Clemens Brunner is a Researcher at the Institute of Psychology within the Faculty of Natural Sciences at the University of Graz. His work bridges electrical/biomedical engineering and cognitive neuroscience, specializing in the neural mechanisms of arithmetic processing and numerical cognition. He actively develops open-source neuroimaging tools used globally in EEG research and sleep analysis. His research focuses on EEG oscillations, biosignal processing, and machine learning applications in cognitive neuroscience. Key interests include arithmetic fact learning, neural correlates of numerical order processing, and non-invasive brain stimulation effects on mathematical cognition. His expertise spans Python programming, statistical analysis, and contributions to major scientific libraries like scikit-learn and SciPy. Analysis of his recent publications reveals consistent emphasis on electrophysiological signatures of arithmetic processing, with growing integration of computational methods and neuromodulation techniques. His work demonstrates strong methodological innovation through open-source software development for EEG analysis and sleep staging. Brunner contributes to the University of Graz's "Brain and behavior" research network, developing tools like MNELAB, SleepECG, and XDF.jl that enhance reproducibility in neuroscience. His collaborations extend to major projects including MNE-Python and BNCI Horizon 2020, advancing brain-computer interface methodologies and neuroimaging standards.