جست‌وجوی استاد و پژوهشگر

Hans-Peter Seidelمشاهده پروفایل

استاد

• Computer Graphics
• 3D Image Analysis
• Digital Geometry Processing
• +۳ مورد دیگر

Hans-Peter Seidel is a leading academic in computer graphics, serving as Director of the Max Planck Institute for Informatics and Full Professor at Saarland University since 1999. Previously held roles include Full Professor at University of Erlangen (1992–1999) and Assistant Professor at University of Waterloo (1989–1992). Holds a PhD in Mathematics (1987) and Habilitation in Informatics (1989) from University of Tübingen. Research focuses on 3D image analysis, digital geometry processing, visual computing, and free viewpoint rendering. Key achievements include pioneering work in surface editing, motion capture, and multi-view video processing. Has organized major conferences like Eurographics and SIGGRAPH, serving as editor for journals including IEEE TVCG and Computer Aided Geometric Design. Recipient of the Eurographics Distinguished Career Award (2012), Gottfried Wilhelm Leibniz Prize (2003), and numerous fellowships. Led initiatives such as the Cluster of Excellence on Multimodal Computing and Interaction (M2CI) and the Max Planck Center for Visual Computing and Communication (MPC-VCC). Active in academic leadership roles including Eurographics Chair and DFG committees. Publications span over 30 SIGGRAPH and 50 Eurographics contributions, with an h-index of 62 and 14,000+ citations. Recognized as a top-cited researcher in computer graphics. Current research explores advanced visualization techniques and geometric modeling innovations.

• Environmental Biotechnology
• Wastewater Treatment
• Anaerobic Digestion
• +۹ مورد دیگر

Werner Fuchs is an Associate Professor at the Institute of Environmental Biotechnology, Department of Agricultural Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU). He is based in Tulln an der Donau and is actively engaged in research and teaching in environmental biotechnology, with a focus on wastewater treatment, biogas, and resource recovery. His research interests center on sustainable environmental technologies, particularly anaerobic digestion, nutrient and energy recovery from waste streams, membrane bioreactor systems (including the MESH filtration process), syngas fermentation, biohydrogen production, and CO₂ sequestration using enzymatic methods. His work bridges fundamental microbiology with applied engineering for circular economy solutions. The recent publications highlight a strong trend toward innovative bioconversion processes, including electro-fermentation, microbial electrolysis cells, artificial microbial consortia, and trickle-bed bioreactors for gas fermentation. These works reflect an interdisciplinary approach combining biotechnology, chemical engineering, and environmental science to address climate change and resource scarcity. Dr. Fuchs has led and participated in numerous research projects funded by the EU (e.g., ManureEcoMine, FABbiogas), FFG, and industry partners, focusing on biogas innovation, nutrient recovery, and waste valorization. He has supervised multiple master’s and doctoral theses, contributing to academic training in the field. He is actively involved in knowledge transfer, having authored popular science articles, technical reports, and delivered lectures at national and international conferences on topics such as biogas technology, digestate treatment, and membrane applications in water and wastewater management.

• Numerics of Partial Differential Equations
• Computational Micromagnetism
• Optimal Mesh Refinement
• +۳ مورد دیگر

Michael Feischl is a Univ. Prof. at TU Wien's Institute for Analysis and Scientific Computing (E101). He specializes in numerical methods for partial differential equations, computational micromagnetism, and optimal adaptivity. Feischl leads the ERC Consolidator Project 'New Frontiers in Optimal Adaptivity' and has held academic positions at TU Wien, University of Bonn, and Karlsruhe Institute of Technology. His research interests span stochastic perturbations, finite element methods, and machine learning applications in computational mathematics. Feischl's work includes groundbreaking contributions to adaptive finite element methods, optimal mesh refinement strategies, and the numerical analysis of the Landau-Lifshitz-Gilbert equation in micromagnetics. His recent publications focus on advancing computational techniques for PDEs, neural operator networks, and stochastic collocation methods. He has developed algorithms with guaranteed convergence properties and optimal complexity, contributing to both theoretical and applied aspects of computational science. Education: Dipl.-Ing. Dr.techn. (PhD in Technical Mathematics) from TU Wien Awards: ERC Consolidator Grant 2022 Labs/Teams: Heads the 'Computational PDEs' research group at TU Wien's Institute for Analysis and Scientific Computing

Camille Schreckمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Physics-based Simulation
• Geometric Modeling
• +۲ مورد دیگر

Camille Schreck is a researcher in Computer Graphics currently holding an Inria Starting Faculty Position (ISFP) at Inria Nancy within the MFX Team. She has been actively contributing to the field of computer graphics with a focus on physics-based simulation and geometric modeling since completing her PhD in 2016. Her educational background includes an engineering degree from ENSIMAG (Grenoble INP) in 2013, followed by a PhD at the University of Grenoble-Alpes supervised by Stefanie Hahmann and Damien Rohmer. Between 2016 and 2020, she conducted postdoctoral research at IST Austria in Chris Wojtan's group. Dr. Schreck's research spans physics-based simulation of natural phenomena, geometric modeling, and computational fabrication techniques. Her work demonstrates particular expertise in simulating deformable materials like paper, water dynamics, and developing novel methods for 3D printing and shape manipulation. She has successfully bridged theoretical computer graphics with practical applications in digital fabrication. Her publication record shows consistent high-impact contributions to top computer graphics venues including SIGGRAPH, Eurographics, and Computer Graphics Forum, with recent work focusing on star-shaped particle simulation, self-shaping 3D printed structures, and efficient mesh processing techniques. The progression of her research demonstrates a clear trajectory from fundamental paper simulation to increasingly complex physical phenomena and fabrication methods. Young Research Fellow of Eurographics France (YFR EGFR) - 2024 Dr. Schreck serves on numerous program committees including SIGGRAPH, Eurographics, and Shape Modeling International. She teaches courses in computer graphics and parallelism at ENSG-GeoRessources and Telecom Nancy, both part of Université de Lorraine. Her teaching spans from 2020 to the current 2024-2025 academic year. As a member of the MFX research team at LORIA (Inria Nancy), she collaborates on advancing the state of the art in physics-based animation and geometric modeling, with her StarDEM project representing a significant contribution to particle simulation methods.

Michael Quellمشاهده پروفایل

پژوهشگر

• Semiconductor Technology
• Computational Engineering
• Numerical Methods
• +۳ مورد دیگر

Michael Quell is a Researcher at the Microelectronics Research Department (E360-01) at TU Wien. His work focuses on numerical methods for semiconductor process simulation, including level-set techniques, hierarchical mesh processing, and high-performance computing. He holds a Dipl.-Ing. (Master's equivalent) and a Dr.techn. (PhD) in technical sciences. His research emphasizes parallel algorithms for material flow simulation, adaptive mesh refinement, and TCAD applications. Education: Dipl.-Ing. and Dr.techn. in Technical Sciences Research interests span computational engineering, numerical analysis, and semiconductor fabrication modeling. Key contributions include shared-memory parallel implementations of the Fast Marching Method, hierarchical re-distancing algorithms, and feature detection for topography simulations. His work often addresses challenges in nanoscale fabrication processes and multi-material wet etching. Collaborations involve projects on parallel mesh adaptation frameworks and quantum transport simulations. He has contributed to advancing computational tools for semiconductor process design and manufacturing optimization.

Manuel Bergerمشاهده پروفایل

مدرس

• Fluid Dynamics
• Medical Engineering
• Computational Fluid Dynamics (CFD)
• +۵ مورد دیگر

Manuel Berger is a Lecturer at the MCI Management Center Innsbruck, specializing in Fluid Dynamics and Medical Engineering. He holds a PhD in Image Guided Diagnosis and Therapy (IGDT) from the Medical University of Innsbruck (2021) and advanced degrees in Mechatronics/Mechanical Engineering (M.Sc., 2014) and Mechatronics (B.Sc., 2011). His academic journey includes roles as a scientific staff member (2014–2024) and dissertant at MCI. He has taught courses such as Advanced Computational Modeling, Medical Image Processing, and Fluid Dynamics. His research focuses on fluid dynamics applications in medical technologies, including nasal airflow simulations, hydrocyclone optimization, and biomedical device development. He has pioneered tools like a sensorized guide wire for cardiovascular surgery and CFD-based pre-surgery planning for nasal interventions. His work also addresses environmental challenges, such as biogas production from waste and microplastic separation. Berger has received awards including the MCI Teaching Award (2024) and the Wilhelm-Auerswald-Preis (2022 finalist). He actively supervises bachelor’s and master’s theses on topics ranging from CFD applications to renewable energy systems. His research group collaborates on projects like plasma actuation studies, hydrocyclone scale-up, and AI-driven aerodynamic analysis. Additional expertise includes fluid mechanics in hydropower, laser anemometry validation, and interdisciplinary education initiatives. He is currently pursuing Chinese language training and has conducted research stays in Taiwan via an OeAD scholarship (2022).

Martin Fedaمشاهده پروفایل

پژوهشگر

• Radiosity
• Photorealistic Image Synthesis
• Parallel Graphics Algorithms
• +۱ مورد دیگر

Martin Feda is an Associated Researcher at the Institute of Computer Graphics, Vienna University of Technology, where he previously served as Assistant Professor. His research focuses on advancing radiosity methods for photorealistic image synthesis, with significant contributions to algorithmic efficiency and visual quality in global illumination rendering. Feda's primary research interests include radiosity, photorealistic image synthesis, and parallel graphics algorithms. He has pioneered techniques for stochastic radiosity, progressive refinement, and parallel implementations to accelerate computation. Key innovations involve hierarchical subdivision algorithms, methods for reducing shadow leaks without explicit meshing, improvements to intermediate radiosity images through directional light, and overshooting techniques to speed up progressive radiosity. His work consistently bridges theoretical advancements with practical applications for handling highly complex scenes. Analysis of his 1991-1997 publication record reveals a clear evolution in radiosity research: early work established parallel implementations on transputers and foundational radiosity algorithms, while later contributions developed sophisticated stochastic and hierarchical methods. The trajectory shows increasing emphasis on Monte Carlo techniques and computational optimizations to achieve greater efficiency and visual fidelity in global illumination, with consistent publication in top-tier graphics venues like Eurographics and Computer Graphics Forum.

• Reconfigurable Computing
• Parallel Computing
• FPGA Accelerators
• +۴ مورد دیگر

Prasanna Viktor is a Professor of Electrical and Computer Engineering and Computer Science at the University of Southern California (USC), holding the Charles Lee Powell Chair in Engineering. He also serves as Director of the Center for Energy Informatics and has held leadership roles in interdisciplinary research centers such as the USC Infosys Center for Advanced Software Technologies. With a BE from Bangalore University, ME from Indian Institute of Science, and PhD from Pennsylvania State University, he is a globally recognized expert in reconfigurable computing, FPGA accelerators, and parallel computing. His research focuses on high-performance architectures for applications in networking, security, HPC, and machine learning. Over 25 years, he has secured research grants totaling over $50M, including $12.9M from 2016–2021. He has advised over 70 doctoral students and published over 600 papers, earning 22 best paper awards. His work has led to IP cores with improved throughput, latency, and energy efficiency. Prasanna is a Fellow of the IEEE, ACM, and AAAS, and an elected member of Academia Europaea. He has received prestigious awards such as the W. Wallace McDowell Award (2015) and the Distinguished Alumnus Award from IISc (2019). He currently serves as Editor-in-Chief of the Journal of Parallel and Distributed Computing. He leads interdisciplinary efforts in energy informatics and smart oilfield technologies, bridging computer science, engineering, and energy sectors. His contributions include foundational work in reconfigurable computing and FPGA-based accelerators for diverse applications.

• Sensors Technology
• Electromagnetic Modeling
• Thermal Systems
• +۳ مورد دیگر

Roman Beigelbeck is a Researcher at the University for Continuing Education Krems, affiliated with the Center for Modelling and Simulation. He specializes in sensor technology, electromagnetic systems, and thermal modeling. His work focuses on advanced sensor development for applications in energy efficiency, aerospace, and biomedical engineering. Current research includes leading the Correlated Analysis System for in-vivo Inspection of Semiconductor Process Wafers (FFG-funded, 2022–2025). He has contributed to projects like optimizing building energy efficiency via non-invasive sensors and advancing MEMS thermal wind sensor accuracy. His expertise spans computational materials science, electromagnetic shielding, and nanomechanical actuation. Publications highlight contributions to Measurement Science and Technology , IEEE Antennas and Propagation Magazine , and MDPI Sensors . Key topics include electric field sensor design, Faraday cage shielding efficiency, and thermal flow sensor optimization. His lectures include advanced thermal models for LED modules and bulk viscosity sensing at international conferences. Notable collaborations involve FFG-funded projects and academic partnerships, such as TU Wien and TU Sofia. His work bridges theoretical modeling with practical industrial applications, emphasizing innovation in sensor technology and computational methods.

Markus Steinbergerمشاهده پروفایل

دانشیار

• GPU Computing
• Parallel Algorithms
• Real-Time Rendering
• +۵ مورد دیگر

Markus Steinberger is an Associate Professor at Graz University of Technology (TU Graz), leading the GPU Computing and Visualization Group at the Institute for Computer Graphics and Vision. He holds a PhD (2013) and Habilitation (2020) in Computer Science from TU Graz. His research focuses on GPU scheduling, parallel computing, real-time rendering, and procedural content generation. He has held roles including Assistant Professor (2015–2021) and Director of Cloud Rendering at Huawei (2021–present). Education: MSc (2010), PhD (2013), Habilitation (2020) in Computer Science from TU Graz PostDoc and Research Positions: NVIDIA (2013–2014), Max Planck Institute (2015–2017) Research interests include dynamic resource scheduling, GPU algorithms, and high-performance visualization. His work has been recognized with awards such as the GI Dissertation Prize (2014), Eurographics Best Paper (2021), and the Heinz Zemanek Prize. Key Projects: Cloud-native rendering, procedural planet rendering, and GPU-optimized algorithms Advising includes PhD student Karl Haubenwallner. His lab explores cutting-edge techniques in real-time graphics and parallel computing.

Zhang Junمشاهده پروفایل

استاد

• Biological Physics
• Nonlinear dynamics and complex systems
• Soft matter physics
• +۴ مورد دیگر

Zhang Jun is a Full Professor of Physics and Mathematics and Co-director of the Applied Math Lab at the Courant Institute, New York University (NYU), USA. He also serves as Co-director of the NYU-ECNU Joint Physics Research Institute in Shanghai, China, and holds an Affiliated Professorship at NYU Shanghai. His research focuses on experimental fluid physics, particularly fluid-structure interactions in biological and geophysical contexts, including bio-locomotion, flapping wings, and continental dynamics. Zhang has authored over 290 invited talks and peer-reviewed papers in journals like Nature and Physical Review Letters. He received the 2017 APS Fellow award for pioneering work in fluid-structure interactions. Beyond academia, he is a freelance illustrator with plans to publish a book of sketches. Education: PhD in Physics (1994), Niels Bohr Institute, University of Copenhagen PhD Candidate (1990-1991), Hebrew University of Jerusalem BSc in Physics (1985), Wuhan University Research Interests: Zhang’s work bridges physics, biology, and geophysics, exploring phenomena like flapping wing aerodynamics, animal locomotion, and Earth’s core-mantle interactions. His experiments often use novel fluid dynamics setups to model natural systems. Awards: APS Fellow (2017) Milton Van Dyke Award (2014) Antarctica Service Medal (2015) Labs & Teams: Co-directs the Courant Institute’s Applied Math Lab, specializing in fluid dynamics experiments. Collaborates with institutions globally, including NYU Shanghai and Aix-Marseille University.

• Computer Vision
• Medical Informatics
• 3D Scene Understanding
• +۵ مورد دیگر

Overview Pedro Hermosilla Casajus is an Assistant Professor at the Department of Computer Vision within the Faculty of Informatics at Technische Universität Wien (TU Wien). His research focuses on advanced computer vision techniques with applications in medical imaging, 3D scene understanding, and deep learning methodologies. He is actively involved in teaching multiple courses including Fundamentals of Computer Vision, Deep Learning for Visual Computing, and Scientific Research and Writing. Projects & Collaborations MyeFLOW (2020–2025) : Developing automated analysis systems for flow cytometry data. EVOCATION (2018–2022) : Real-time shape acquisition technologies. Modeling the World at Scale (2020–2026) : Large-scale 3D modeling techniques. Research Highlights His work bridges computer vision with medical diagnostics, particularly in measurable residual disease detection using flow cytometry. He explores geometric deep learning for 3D point cloud analysis and scene graph generation, advancing unsupervised semantic segmentation methods. Recent contributions include stylized Gaussian splatting for neural rendering and open-vocabulary 3D scene understanding frameworks. Teaching He teaches core courses like Fundamentals of Computer Vision and supervises student projects in medical informatics, visual computing, and human-centered computing.

• Open Data
• Data Quality
• Knowledge Graphs
• +۳ مورد دیگر

Dr. Sebastian Neumaier is a Senior Researcher at the Institute of IT Security Research within the Department of Computer Science and Security at University of Applied Sciences St. Pölten . He focuses on open data ecosystems, knowledge graphs, and semantic web technologies. Research Interests : Open Data Quality and Governance Knowledge Graph Construction Data Security and Usage Control Semantic Web Standards Smart City Data Infrastructure Publication Trends (2015–2025) span open data quality assessment, knowledge graph applications, cybersecurity in data spaces, and semantic data labeling. Key subfields include license compliance, spatio-temporal data systems, and decentralized dataset exchange architectures. Education : PhD (2019) – Semantic Enrichment of Open Data Master's Thesis – Data Intelligence BSc – Computer Science Labs & Projects : Core contributor to ADEQUATe platform for open data quality Co-developer of DALICC as a service for license clearance Active in data space policy frameworks Participant in EU digital product passport initiatives

Li Keqinمشاهده پروفایل

استاد

• Computer Networking
• Heterogeneous Computing Systems
• Computer Architectures and Systems
• +۶ مورد دیگر

Professor Keqin Li is a globally recognized academic holding concurrent professorships at Hunan University (China) and State University of New York (USA). He has held distinguished titles including National Distinguished Professor and SUNY Distinguished Professor. His research focuses on computer networking, heterogeneous systems, energy-efficient computing, and distributed systems. He has authored over 800 publications with an h-index of 64 and secured major grants from Chinese National Science Foundation and Ministry of Science and Technology. Education: PhD in Computer Science from University of Houston (1990), B.S. from Tsinghua University (1985). Research Interests: Includes parallel computing architectures, cloud-edge computing integration, energy-efficient algorithms, and task scheduling optimization. His work spans foundational studies to applied solutions in distributed systems, with notable contributions to network function virtualization and secure cloud data sharing. Awards: Ranked top globally in distributed computing by Scopus citation metrics (2020-2021) IEEE Fellow (2015) Recipient of 1000 Plan Chinese Talent Program (2013) Professional Activities: Editorships at ACM Computing Surveys, IEEE Transactions on Parallel and Distributed Systems, and over 190 conference organizing roles. Principal Investigator of 12+ major research projects (2013-2025). Labs/Teams: Leads research groups focused on parallel computing, cloud-edge systems, and energy-efficient architectures across multiple institutions.

Wolfgang Ringمشاهده پروفایل

استاد

• Inverse Problems
• Partial Differential Equations
• Shape Optimization
• +۳ مورد دیگر

Wolfgang Ring is a professor at the University of Graz , affiliated with the Institute of Mathematics . His work bridges applied mathematics and engineering disciplines. Research Interests Specializing in inverse problems , his research spans: Partial differential equations and variational inequalities Shape and structural optimization Nonsmooth optimization methods Ill-posed Volterra equations Image processing and analysis His mathematical techniques address challenges in electromagnet design , mechanical systems , and medical imaging applications. Academic Contributions Key publication trends include: Development of regularization methods for ill-posed problems Advancements in predictor-corrector algorithms for Volterra equations Innovations in shape optimization using finite element techniques Structural analysis of total variation regularization solutions Education Dr. techn. in Mathematics from Technical University Graz (1993) Teaching Has taught graduate-level courses on: Ordinary differential equations Complex analysis Heat and mass transfer