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Torsten HoeflerView profile

Professor

• Deep learning Systems
• Parallel programming models
• High performance and datacenter networking
• +8 more

Torsten Hoefler is a Full Professor of Computer Science at ETH Zurich, Switzerland, with an adjunct appointment in Electrical Engineering. He previously held roles at the National Center for Supercomputing Applications (University of Illinois at Urbana-Champaign) and Indiana University. Full Professor of Computer Science, ETH Zurich (2020–present) Adjunct Professor of Electrical Engineering, ETH Zurich (2020–present) Member at Large, ACM SIGHPC Executive Committee (2013–present) Leadership roles in the MPI Forum and Blue Waters project His research focuses on performance-centric system design , with emphasis on scalable networking, parallel programming models, and performance modeling. Key contributions include the Slim Fly network topology, Data-Centric Python framework, and innovations in parallel graph computations and RDMA-based systems. Recent publications span topics like LLM training networks , quantization geometry , chiplet interconnects , and AI-driven climate modeling , reflecting his interdisciplinary approach combining HPC, AI, and hardware-software co-design. ACM Gordon Bell Prize (2019) ERC Consolidator Grant (2020) IEEE TCSC Award for Excellence (2019) SIAM SIAG/SC Junior Scientist Prize (2012) Latsis Prize of ETH Zurich (2015) He has received multiple best paper awards at top conferences (SC10, SC13, SC14, SC19, IPDPS'15, HPDC'15, OOPSLA'16) and contributed to MPI-3 standardization.

• Machine Learning
• Computational Biology
• Medical Informatics
• +9 more

Günter Klambauer is a Professor at the Institute for Machine Learning , Johannes Kepler University Linz, and leads the LIT Artificial Intelligence Lab in Austria. His research bridges artificial intelligence with life sciences , focusing on deep learning applications in retinal imaging , drug discovery , and hydrological modeling . Affiliation: JKU Institute for Machine Learning & LIT Artificial Intelligence Lab Key Research Areas: Medical Imaging AI, Biological Sequence Modeling, Generative Models for Molecules, Time-Series Forecasting His recent publications highlight extended LSTM architectures (xLSTM) for biological sequence modeling, contrastive learning in retinal imaging, and in-context learning for low-data drug discovery. He has pioneered frameworks like TiRex for zero-shot forecasting and LaM-SLidE for spatial dynamical systems. Scientific Awards: Austrian Life Science Award (2012) Award of Excellence (2014) ELLIS Society Scholar (2020) Director, ELLIS Machine Learning for Molecules Discovery Program (2023) Professor Klambauer collaborates extensively on AI-driven biomedical projects , including retinal image analysis and antibody design, while advancing foundational neural network architectures for diverse domains from healthcare to climate modeling.

Diana MarinView profile

Researcher

• Computer Graphics
• Computational Geometry
• Point Cloud Processing
• +3 more

Diana Marin is a PostDoc Researcher at TU Wien's Institute of Visual Computing & Human-Centered Technology. She holds a BSc, MEng, and Dr.techn. (PhD) in technical fields. Her research focuses on computational geometry, point cloud processing, and distributed computing for large-scale datasets. She has contributed to projects like Distributed Surface Reconstruction and RE:STOCK INDUSTRY. Education: BSc, MEng, Dr.techn. (PhD) Her work emphasizes curve and surface reconstruction from unorganized point clouds, leveraging proximity graphs and distributed computational methods. Key projects include optimizing surface reconstruction for massive datasets and developing parameter-free algorithms for connectivity analysis. Her publications span topics like SING neighborhood graphs, Riemannian manifold curve reconstruction, and distributed processing techniques. She collaborates on projects such as PostDisaster and Mixed Reality Lab.

Bart De MoorView profile

Professor

• Numerical Linear Algebra
• Optimization
• Algebraic Geometry
• +11 more

Bart De Moor is a Full Professor at the Department of Electrical Engineering, KU Leuven, Belgium, and a guest professor at the University of Siena. He leads the STADIUS research group and has supervised 85 PhD students. His roles include chairman of Health House (2016–present), member of the Board of VIB (Biotech Institute), and former Vice-Rector for International Policy (2009–2013). Education: Master Degree in Electrical Engineering (1983), KU Leuven PhD in Engineering (1988), KU Leuven Research Interests: His work spans numerical linear algebra, optimization, algebraic geometry, systems and control theory, data-driven AI, machine learning, and applications in process industry and biomedical big data. He has contributed to subspace identification, tensor decomposition, bioinformatics, and quantum computing. Publications Trends: His publications highlight subspace identification methods, tensor decomposition, bioinformatics, and biomedical data analysis. These reflect interdisciplinary advancements in control theory, quantum physics, and mathematical engineering, with applications in industrial and healthcare domains. Scientific Awards and Honors: Leslie Fox Prize (1989) Laureate of the Belgian Royal Academy of Sciences (1992) Bi-annual Siemens Award (1994) Fellow of IEEE (since 2004) Member of the Royal Academy of Belgium for Science and Arts (since 2000) Fellow of IFAC (since 2022) Commander in the Order of King Leopold I (2020) Fellow of SIAM (since 2017) FWO Excellence Award (2010) Advising and Grants: He has led a research group of 20 PhD students and postdocs, co-founded 8 spinoff companies, and secured the ERC Advanced Grant ‘Back to the roots’ (2020–2025). He also co-holds the KU Leuven Chair on healthcare systems (2018–present). Labs and Organizations: Active in the STADIUS research group (KU Leuven), he has served on boards of the Flemish Interuniversity Institute for Biotechnology (VIB), the Alamire Foundation, and the Health Tech Experience Center Health House. His spinoffs include Trendminer, Cartagenia, and Ugentec.

Andreas StollwitzerView profile

Researcher

• Railway Engineering
• Structural Dynamics
• Civil Engineering
• +3 more

Andreas Stollwitzer is a researcher affiliated with the Research Area Steel Construction at TU Wien. His academic titles include Univ.Ass. (University Assistant), Dipl.-Ing. (Diplom-Ingenieur), and Dr.techn. (Doctor of Technical Sciences). His research focuses on railway bridge dynamics, track-bridge interaction, and structural health monitoring. Key areas of investigation include the behavior of ballasted tracks on railway bridges, dynamic characteristics of bridge-track systems, and vibration analysis in high-speed rail infrastructure. His work emphasizes experimental and numerical methods to study phenomena such as longitudinal/lateral track-bridge interaction, dynamic stiffness and damping measurement, and destabilization of ballast beds under vertical vibrations. He has contributed to projects like DYS-GROS, analyzing the dynamic interaction between track components and bridge structures through both simulations and in-situ testing. Recent publications (2021–2023) highlight advancements in damping factor calculations, comparison of vehicle-bridge interaction approaches, and the application of indirect structural health monitoring techniques using vehicle-based sensors. His findings aim to improve bridge safety, reduce computational uncertainties in dynamic analyses, and optimize railway infrastructure design under high-speed conditions. He collaborates with institutions and researchers in Austria and internationally, focusing on railway engineering challenges. While no formal awards are listed, his extensive publication record reflects significant contributions to civil engineering dynamics and infrastructure systems.

Michael WimmerView profile

Professor

• Computer Graphics
• Real-Time Rendering
• Procedural Modeling
• +4 more

Michael Wimmer is a Full Professor at TU Wien, leading the Rendering and Modeling Group and directing the Center for Geometry and Computational Design. He holds a M.Sc. (1997) and Ph.D. (2001) from TU Wien. His research focuses on real-time rendering, procedural modeling, computational design, and point-based graphics. He has co-authored over 200 papers and the book *Real-Time Shadows*. He serves as Co-Editor-in-Chief of Computer Graphics Forum , chairs SIGGRAPH Asia 2025, and received the Eurographics Outstanding Technical Contributions Award (2023). Education: M.Sc. in Computer Science (1997), TU Wien Ph.D. in Computer Science (2001), TU Wien Research Interests: Real-time rendering and visualization Procedural modeling and computational design Point-based graphics and neural rendering Applications in computer games and urban environments Awards: Eurographics Outstanding Technical Contributions Award (2023) Wolfgang Straßer Award (Best Paper, 2022) Eurographics Fellow (2018) Outstanding Service Award (2012) Advising & Grants: Coordinator of the Special Research Programme Advanced Computational Design Key researcher at VRVis Research Center Labs & Teams: Rendering and Modeling Group Center for Geometry and Computational Design

• Computer graphics
• Geometry processing
• Computer-aided geometric design
• +6 more

Leif Kobbelt is a Full Professor of Computer Science and Head of the Visual Computing Institute at RWTH Aachen University . He previously held academic positions at the Max-Planck-Institute for Computer Science, University of Erlangen-Nürnberg, and University of Wisconsin-Madison. Diploma in Computer Science (1992), Karlsruhe Institute of Technology PhD in Computer Science (1994), Karlsruhe Institute of Technology His research focuses on computer graphics and geometry processing , with specific interests in 3D reconstruction, quad mesh generation, real-time rendering, and geometric modeling algorithms. He has pioneered techniques for efficient mesh processing, anisotropic geodesic computation, and procedural facade visualization. Recent publications analyze nonlinear constraints in geometric modeling, quad layout optimization, and real-time rendering techniques. Key themes include mesh parameterization, multiresolution analysis, and computational geometry for interactive applications. Scientific recognitions include: 2014 Gottfried Wilhelm Leibniz Prize (Germany's most prestigious research award) 2013 ERC Advanced Grant (ACROSS project) 2008 Eurographics Fellow 2004 Eurographics Outstanding Technical Contribution Award 2000 Heinz-Maier-Leibnitz Award He leads major research initiatives like the excellence clusters UMIC (€40M) and AICES (€15M), and the ERC-funded ACROSS project (€2.5M, 2014-2018). He serves as principal investigator and reviewer for international journals and organizations.

Mike BurtonView profile

Professor

• Volcanology
• Petrology
• Remote Sensing
• +4 more

Mike Burton is the Chair in Volcanology at the School of Earth and Environmental Sciences, University of Manchester . Since 2015, he has led the Geoscience Group, comprising 13 permanent academic staff, and directs a research team of 3 postdoctoral researchers, 3 PhD students, and a senior research fellow. He also serves on the School Senior Leadership Team, shaping institutional strategy and research direction. He earned a BSc in Chemical Physics from the University of Sussex in 1993 and a PhD in Atmospheric Chemistry from the University of Cambridge in 1999. His early career included postdoctoral research at Cambridge and research roles at INGV in Catania and Pisa, Italy, before returning to the UK in 2015. His research integrates volcanology , petrology , remote sensing , and gas geochemistry to improve eruption forecasting and volcanic hazard management. He uses ground-based and satellite observations, numerical modeling, and field experiments to study volcanic degassing, magma ascent, and volatile cycling. He has pioneered the use of SO2 cameras and open-path FTIR systems for real-time volcanic gas monitoring. His recent publications span mafic eruption dynamics , CO2 flux quantification , tephra microstructure , and remote sensing of volcanic plumes , often in collaboration with volcano observatories and international partners. These works reflect a consistent focus on integrating observational data with modeling to understand volcanic behavior and its environmental impact. Scientific Recognition: ERC Consolidator Grant (CO2Volc, €1.72M) NERC Large Grant (DisEqm, £3.5M) University of Manchester Researcher of the Year (2017) President, GMPV Division, European Geosciences Union (2015–2018) Fellow of the Geological Society (2016–present) Invited/keynote speaker at AGU, EGU, and other major conferences Leadership & Advisory Roles: Member, Foreign Office Scientific Advisory Committee (UK volcanism hazards) Former Chief Scientist, Stromboli Volcano Observatory (2002/03 crisis) Led INGV Catania gas monitoring team (2002–2008) External PhD examiner for Cambridge and Montreal Reviewer for Nature, Science, EPSL, JVGR, and funding agencies (NERC, NSF, EU) Research Platforms & Collaborations: He is affiliated with the Manchester Environmental Research Institute , Sustainable Futures , and Digital Futures research platforms. He maintains active collaborations with INGV (Italy), NSF (USA), and multiple European institutions, and has co-supervised joint PhD students.

• Probabilistic Combinatorics
• Extremal Combinatorics
• Random Structures
• +1 more

Michael Krivelevich is a Full Professor at the School of Mathematical Sciences, Tel Aviv University, holding this position since 2005. He previously served as Associate Professor (2002-2005) and Senior Lecturer (1999-2002) at the same institution. From 2015 to 2020, he acted as Dean of the Faculty of Exact Sciences at Tel Aviv University. Research Interests: Probabilistic and extremal combinatorics Random structures Applications of combinatorics to computer science Scientific Contributions: Authored two books: Positional Games (2014) and Random Graphs, Geometry and Asymptotic Structure (2016) Published over 200 research papers in combinatorics and related fields Editor-in-Chief of the Journal of Combinatorial Theory Series B (JCTB) Recognitions: Clay Lecturer (2019) Fellow of the American Mathematical Society (2017) Invited Speaker at ICM (2014) Pazy Memorial Award (2007) Academic Leadership: Dean of Faculty of Exact Sciences (2015-2020) Supervised 9 PhD and 16 MSc students at Tel Aviv University

Michael WimmerView profile

Professor

• Computer Graphics
• Real-Time Rendering
• Point Clouds
• +4 more

Univ.Prof. Michael Wimmer is a Professor in the Department of Computer Graphics and Visualization at TU Wien's Faculty of Informatics. His research focuses on real-time rendering, point cloud processing, GPU computing, and computational design. He leads projects involving architectural visualization, thermal simulation, and integrative design frameworks combining 4D sketching with material modeling. His work bridges computer graphics with applications in architecture and engineering. ORCID: 0000-0002-9370-2663 Research Group: Network Lab Recent research emphasizes GPU-accelerated algorithms (e.g., LOD generation for 2 billion points), real-time rendering techniques, and deep learning approaches for surface reconstruction. Collaborations span thermal simulation with civil engineers and 4D design tools for architects. Notable contributions include: Developing PPSurf for detailed surface reconstruction using point convolutions Advancing Vulkan-based rendering pipelines in academic settings Integrating light polarization for HDR imaging His lab explores applications in architectural design metaphors, computational material assessment via GeoRadar, and thermal simulation using precomputed radiative transport. Students under his supervision focus on GPU optimization, 3D reconstruction, and VR ergonomics.

Antonio Rodríguez-SánchezView profile

Associate Professor

• Explainable AI
• Computational Neuroscience
• Deep Learning
• +4 more

Antonio Rodríguez-Sánchez is an Associate Professor in the Intelligent and Interactive Systems group at the Department of Computer Science, Universität Innsbruck (since 2019). He holds a PhD from York University (2010) and has held academic roles in Austria, Canada, and Spain. His research focuses on Explainable AI, computational neuroscience, deep learning, computer vision, robotics, and medical imaging. Education: PhD in Computer Science, York University (Canada), 2010 M.Sc. in Computer Science, Universidade da Coruña (Spain), 1998 B.Sc. in Computer Science, Universidad de Córdoba (Spain), 1996 3-year Bachelor in Biology, Autonomous University of Madrid (Spain), 1998–2001 Research Interests: His work bridges AI and neuroscience, emphasizing explainable systems, medical imaging analysis, robotics, and deep learning applications. Recent trends in publications highlight advancements in healthcare AI (REM sleep disorder prediction), robotic recycling, and computer vision for environmental monitoring. Teaching & Advising: Teaches courses like Deep Learning, Computer Vision, and Algorithms. Supervises PhD/MSc students (e.g., Safoura Rezapour-Lakani, Sebastian Stabinger). Active in EU-funded projects like PaCMan (FP7-ICT) and IntellAct. Labs & Projects: Leads research in the Intelligent and Interactive Systems group, focusing on interdisciplinary AI applications. Projects include automated avalanche detection and robotic recycling systems.

• Probability Theory
• Financial Mathematics
• Stochastic Processes

Paul Eisenberg is an Assistant Professor at the Institute for Statistics and Mathematics at Vienna University of Economics and Business. He holds a doctorate in Mathematics and has held positions at the University of Liverpool, Vienna University of Technology, and Technical University of Dortmund. His research focuses on probability theory and financial mathematics, particularly stochastic processes, term structure modeling, and applications to financial markets. He teaches courses in Probability, Quantitative Methods, and Business Mathematics. Research outputs concentrate on stochastic processes in finance, including term structure modeling, stochastic optimization, market microstructure, and applications to cryptocurrency markets. Recent work shows emphasis on regime-switching models and high-dimensional stochastic systems.

Hsiang-Yun WuView profile

Research Fellow

• Information Visualization
• Visual Analytics
• Biological Network Visualization
• +13 more

Hsiang-Yun Wu is a Research Fellow at the Computer Graphics department of Vienna University of Technology (TU Wien), actively contributing to information visualization and visual analytics. Her work spans biological network visualization, graph drawing, schematic network maps, and data physicalization, with a focus on interactive techniques and human-centric design. Projects: ArtVis (2022–2027) , SANE (2024–2027) , SMGV-Esprit (2024–2027) , and HumAlgo (2018–2023) . Affiliations: Member of the Visualization Group at TU Wien. Her recent publications emphasize uncertainty visualization, network physicalization, and dynamic graph representations. Notably, she received the EuroVis 2019 Honorable Mention Award for optimizing stepwise animations. Wu supervises diploma theses in areas like metabolic pathway visualization and semantic-aware character animation. Key research trends include integrating biological data with urban-style schematic maps ( Metabopolis ), physicalization workflows for anatomical education ( Slice and Dice ), and mixed labeling strategies in 3D environments.

Herbert EdelsbrunnerView profile

Professor

• Algorithms
• Computational Geometry
• Computational Topology
• +3 more

Herbert Edelsbrunner is a Professor at the Institute of Science and Technology Austria (ISTA) since 2009. He holds dual roles as Arts and Sciences Professor of Computer Science and Professor of Mathematics at Duke University (1999–2012). His research spans computational geometry, topology, and their applications in molecular biology. Edelsbrunner earned his PhD from Graz University of Technology in 1982 and has held faculty positions at the University of Illinois (1985–1999) and Graz University of Technology (1981–1985). His research focuses on algorithms, geometric modeling, and topological data analysis, with contributions to persistence diagrams, alpha shapes, and molecular docking. He leads the Edelsbrunner Group at ISTA, exploring computational geometry and topology in interdisciplinary contexts. Education: PhD in Computer Science, Graz University of Technology, 1982 Assistent at Institute for Information Processing, Graz University of Technology, 1981–1985 Edelsbrunner has received numerous awards, including the Alan T. Waterman Award (1991) and the Wittgenstein Award (2018). His work bridges theoretical foundations with applications in 3D printing, structural biology, and neuroscience.

Martin SchroderView profile

Professor

• Materials chemistry
• Porosity
• Gas adsorption and selectivity
• +5 more

Professor Martin Schroder is a leading materials chemist currently serving as Vice President and Dean of the Faculty of Science and Engineering at the University of Manchester. He previously held executive and academic roles at the University of Nottingham (1995-2015) and the University of Edinburgh (1982-1995), culminating in his appointment as Professor of Chemistry at Manchester (2015-present). His career spans over four decades with significant contributions to porous metal-organic frameworks (MOFs) for energy and environmental applications. PhD in Chemistry from Imperial College London (1978) BSc in Chemistry from the University of Sheffield (1975) Professor Schroder's research focuses on materials chemistry , particularly metal-organic frameworks (MOFs) for gas separation and capture. His work addresses CO2 reduction , toxic gas removal , and proton conductivity through innovative framework design and functionalization. Recent publications highlight MOF applications for hydrogen storage , SO2 capture , and NO2 conversion . His 15 most recent publications (2016-2020) demonstrate sustained expertise in porous materials engineering , showing consistent focus on gas adsorption mechanisms , supramolecular interactions , and environmental remediation through MOF technology. Key trends include CO2 selectivity , dynamic framework behavior , and electrochemical sensor development . Awarded numerous honors including: Royal Society of Chemistry Nyholm Prize (2020) Tilden Lectureship & Medal (2001/02) Multiple RSC awards (2003, 2008) Honorary Doctorates (2005, 2017) Fellowships (FRSE, FRSC) He has organized major international conferences like the 1st International Conference on Metal-Organic Frameworks (2008) and led the Royal Society Discussion Meeting on 'The New Chemistry of the Elements' (2014). His work bridges fundamental inorganic chemistry with practical solutions for clean air technologies and carbon capture .