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Wieland KonradView profile

Researcher

• Software Engineering
• Model-Driven Engineering
• Collaborative Systems
• +3 more

Wieland Konrad is a researcher affiliated with the Institut für Softwaretechnik und Interaktive Systeme at TU Wien. His work focuses on model-driven engineering, software versioning, and collaborative systems. He has extensively contributed to advancing model versioning techniques, conflict resolution in software models, and UML-based solutions. His research emphasizes practical applications in software development lifecycle management and educational methodologies for UML. Key research areas include: Model versioning systems and semantics Conflict detection and resolution algorithms Collaborative cross-organizational modeling EMF/UML profile-based extensions Software evolution analysis His publications highlight advancements in concurrent modeling tools like Colex, adaptable versioning frameworks, and educational strategies for large-scale UML teaching. While no awards are listed, his prolific output since 2009 demonstrates sustained academic contribution.

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.

Lukas EinkemmerView profile

Professor

• Numerical Analysis
• Plasma Physics
• Computational Mathematics
• +3 more

Prof. Lukas Einkemmer is a faculty member at the University of Innsbruck, holding a position in the Institute of Mathematics. He specializes in numerical analysis, plasma physics, and high-performance computing. His work focuses on developing advanced numerical methods for solving complex kinetic equations and PDEs, with applications in plasma simulation and computational fluid dynamics. Education: He earned a PhD in applied mathematics (2014) and MSc in physics (2013) from the University of Innsbruck, alongside BSc in applied mathematics (2010). He completed research stays at UC Merced and holds notable academic awards, including the SciCADE New Talent Award (2015) and participation in the Heidelberg Laureate Forum (2013). Research & Teaching: His research includes exponential integrators, dynamical low-rank methods, and semi-Lagrangian discontinuous Galerkin schemes. He teaches numerical methods, PDEs, and computational courses at both undergraduate and graduate levels. He also leads training programs in parallel computing (OpenMP/MPI) at the University’s Research Center for High-Performance Computing. Publications & Grants: Over 70 peer-reviewed articles in journals like J. Comput. Phys. and SIAM J. Sci. Comput. , focusing on numerical algorithms and their applications. He has secured grants from FWF and other agencies, advancing methods for plasma physics and kinetic theory. Awards & Recognition: Multiple honors, including the Oberwolfach Leibniz Graduate Student award (2014) and sustained scholarship support for academic excellence.

Corinna BrungsView profile

Researcher

• Phytochemistry
• Biodiscovery
• Mass Spectrometry
• +4 more

Corinna Brungs is a Senior Scientist at the University of Vienna , affiliated with the Faculty of Life Sciences and the Department of Pharmaceutical Sciences (Division of Pharmacognosy). Her research focuses on applying cutting-edge mass spectrometry techniques for natural product identification, biomarker discovery, and untargeted metabolomics workflows. Developing open mass spectral libraries Advancing data processing strategies Specializing in tattoo pigment and metabolite analysis Research Highlights: Brungs bridges phytochemistry and computational metabolomics through method development in mass spectrometry. Her work includes creating standardized protocols for: Tattoo pigment identification In-source fragmentation analysis Non-targeted drug exposure profiling Integration of mobility-resolved spectrometry Scientific Awards: 2025 Early Career Prize (Metabolomics Society) 2025 Early Career Travel Award (Metabolomics Society) 2022 Czech Academy of Sciences Fellowship Publications (2022-2025) demonstrate leadership in: MALDI-TIMS-MS2 bioimaging MZmine 3 software development Metabolomics data reproducibility Mass spectral library matching

Hastad JohanView profile

Professor

• Complexity Theory
• Cryptography
• Approximation Algorithms
• +1 more

Johan Håstad is a Full Professor in the Department of Computer Science at the Royal Institute of Technology (KTH), Sweden, since 1992. Previously, he held academic positions at KTH and the Massachusetts Institute of Technology (MIT) as a Postdoctoral Fellow (1986-1987). His work lies at the intersection of theoretical computer science and mathematics, with foundational contributions to computational complexity theory, cryptography, and approximation algorithms. Ph.D. in Mathematics from MIT (1986) Member of the Royal Swedish Academy of Sciences (2001) Knuth Prize laureate (2018) for breakthroughs in optimization, cryptography, parallel computing, and complexity theory Research Focus: Johan Håstad's research has fundamentally shaped computational complexity theory, particularly in understanding the limits of efficient computation and approximation. His work on probabilistically checkable proofs (PCPs) and hardness of approximation has had a profound impact on theoretical computer science, influencing areas like cryptography and parallel computing. He is known for developing Håstad's switching lemma and establishing strong inapproximability results for NP-hard problems. Scientific Recognition: ACM Doctoral Dissertation Award (1986) Gödel Prize (1994, 2011) Chester Carlson Research Prize (1990) Göran Gustafsson Prize (1999) Knuth Prize (2018)

• Systems
• Concurrency
• Memory Management
• +5 more

Christoph Kirsch is a Professor and Chair of the Department of Computer Science at the University of Salzburg. He also serves as Chair of the Programming Research Laboratory at the Faculty of Information Technology, CTU Prague. His research focuses on systems, concurrency, memory management, and formal methods, with notable contributions including the Selfie educational software project and work on symbolic execution. He is a prolific author with over 50 publications in top venues like LCTES and EMSOFT. Education: Ph.D. in Computer Science (details not specified). His teaching includes courses on elementary computer science concepts and curricula development. He advises students such as Anna Bolotina and has graduated over a dozen PhD students. Research highlights include the Selfie system (self-referential C compiler and emulator), work on concurrency primitives like Scal and Timestamped Stack, and contributions to real-time systems (Logical Execution Time, Variable-Bandwidth Servers). His recent focus includes teaching digital thinking and evaluating eval in R programs. He has organized conferences like MPLR’24 and served on program committees for EuroSys and RTNS. His book Elementary Computer Science emphasizes foundational concepts for broad audiences.

• Database Theory
• Computational Logic
• Parameterized Complexity
• +4 more

Reinhard Pichler is a Full Professor at the Vienna University of Technology (TU Wien), affiliated with the Faculty of Informatics and the Department of Databases and Artificial Intelligence . His research focuses on Database Theory , Computational Logic , and Parameterized Complexity . He leads multiple research projects like DeConquer (2023–2027) and HyperTrac (2018–2022), addressing challenges in query optimization and hypergraph decompositions. He holds the prestigious START Prize (2014–2022) for young researchers. His work spans theoretical foundations (e.g., hypertree decompositions) and practical applications (e.g., SPARQL query processing systems like SparqLog). He contributes to academic governance, serving on faculty councils and curriculum commissions. His research innovations bridge algorithmic theory and real-world database systems, emphasizing efficient query evaluation and tractability analysis. Key contributions include advancing fractional hypertree decompositions , SPARQL query optimization , and consistent query answering . His projects often involve collaborations with industry and international funders like the Austrian Science Fund (FWF) and Vienna Science and Technology Fund (WWTF). He actively publishes in top venues like Journal of the ACM , ACM Transactions on Database Systems , and Proceedings of the VLDB Endowment . His academic leadership extends to course design, teaching advanced topics like Complexity Theory and Theoretical Computer Science . He mentors doctoral students and oversees research teams exploring cutting-edge areas like uncertain databases and cloud-based computational social choice .

Oskar MencerView profile

Professor

• Numerical methods and simulations
• Imaging
• Discretization of space, time and value
• +7 more

Oskar Mencer is a Professor in the Department of Computing at Imperial College London , where he has been a member of academic staff since 2000. He was also a Consulting Professor at Center for Computational Earth and Environmental Science , Stanford University (2009-2010). His research focuses on Multiscale Dataflow Computing , exploring the interaction of hardware and software systems through domain-specific representations, parallel programming, VLSI design, and compiler methodologies. He has contributed to fields including high-performance computing, FPGA optimization, and computational finance. Dr. Mencer's work has been recognized with a Special Award from Com.sult (2012), Imperial College Research Excellence Award (2007), and a Top EPSRC Advanced Fellowship (2001). He has received multiple best paper awards, including at ICFPT'08 and ASAP 2008, and his 2000 paper on stream architectures was recognized as historically significant in 2015. His publications demonstrate a strong emphasis on FPGA acceleration , custom architectures , and parallel processing across geophysics, finance, and neuroscience applications. Special Award for Dataflow Innovation (2012) Best Paper Award - ICFPT'08 Best Paper Award - ASAP 2008 He has served on technical committees for conferences such as FPL , DATE , and FPT , and leads the Computer Architecture Research Group (currently inactive).

Alexandru NicolauView profile

Professor

• Parallelizing compilers
• Supercomputing
• High Performance Computing (HPC)
• +5 more

Alexandru Nicolau is a Distinguished Professor and Chair of the Department of Computer Science at the University of California, Irvine (USA), where he has worked since 1992. He previously held positions as Associate Professor (1988–1992) and Assistant Professor (1984–1988) at UC Irvine and Cornell University, respectively. Education : B.A., Brandeis University (1980) MS (1981), Ph.D. (1984), Yale University Research Interests : A leading expert in parallelizing compilers , high-performance computing , and software-hardware co-design , Nicolau pioneered foundational techniques like Percolation Scheduling and Optimal Loop Parallelization . His work enables efficient exploitation of instruction-level parallelism in general-purpose programs, with applications in embedded systems , matrix algorithms , and GPU-based neural networks . He has also contributed to Electronic Design Automation (EDA) and lightweight synchronization protocols . Scientific Awards : IEEE Fellow (2014) ACM SIGPLAN Most Influential Paper (PLDI 20 years) EDAA/IEEE/ACM DATE Most Influential Paper (10 years) ACM ICS Most Influential Paper (25 years) 4 Best Paper awards (VLSI design 2003, ISHPC 2005, CASES 2008, IJCNN 2009) Advising & Grants : He has mentored notable scholars now at Stanford, McGill, and Google, and secured over $20M in funding from NSF , DARPA , and industry leaders like IBM and Intel . His professional service includes chairing ACM ICS’09 and PPOPP’13, and serving on steering committees for LCPC and ICS. Labs & Collaborations : His techniques have been adopted by IBM Watson, Siemens Munich, Fujitsu Labs Japan, and the open-source GCC compiler.

• Medical Imaging
• MRI Reconstruction
• Real-Time MRI
• +4 more

Martin Uecker is a Professor at the Institute of Biomedical Imaging at TU Graz. His research focuses on advanced MRI reconstruction techniques, real-time imaging, and open-source software tools like the Berkeley Advanced Reconstruction Toolbox (BART). He specializes in developing methods for fast and accurate medical imaging, including applications in cardiac MRI, fetal brain imaging, and disease monitoring. His work emphasizes reproducibility, quantitative imaging, and clinical translation. Key research areas include generative models for MRI reconstruction, model-based inversion of the Bloch equations, and interactive real-time MRI systems. His team collaborates on projects involving hardware-software integration, such as portable MRI scanners and MRI-guided interventions. Notable contributions include advancements in multi-echo radial FLASH techniques, motion-resolved T1 mapping, and Bayesian uncertainty estimation in imaging. Uecker’s publications highlight innovations in accelerating MRI acquisition and reconstruction, with applications in pulmonary function assessment, neonatal imaging, and cardiovascular diagnostics. His work bridges theoretical physics, computational methods, and clinical practice, fostering open-source frameworks to democratize access to cutting-edge imaging tools.

Michael KerberView profile

Professor

• Computational Topology
• Algebraic Topology
• Computational Geometry
• +4 more

Michael Kerber is a Professor at Graz University of Technology, Institute of Geometry, specializing in computational topology and geometry. His research bridges mathematical theory with applications in data analysis, focusing on persistent homology and geometric algorithms. PhD from Max Planck Institute for Informatics (2009) Postdoc positions: Max Planck Institute, Stanford University, IST Austria His work centers on designing efficient algorithms for topological data analysis, particularly: Persistent Homology 2-Parameter Persistence Geometric Filtrations Algebraic Curve Analysis High-Dimensional Sphere Packing Recent publications emphasize: Improved Delaunay bifiltration methods NP-hardness of interleaving distance computation Sparse Čech filtrations for big data Integration with graph neural networks He has co-developed key software tools: PHAT DIPHA HERA SOPHIA

Maximilian BrunnerView profile

Researcher

• Numerics of PDEs
• Finite Element Methods (FEM)
• Contractive Iterative Solvers
• +3 more

Maximilian Brunner is a Postdoc at TU Wien's Institute of Analysis and Scientific Computing (E 101), specializing in Numerics of Partial Differential Equations (PDEs). He holds a Dipl.-Ing. (MSc) and Dr.techn. (PhD) from TU Wien, with his doctoral thesis on On optimal adaptivity for semilinear PDEs earning the 2025 Study Prize from the Austrian Mathematical Society (ÖMG). His research focuses on adaptive finite element methods (FEM), iterative solvers for nonlinear PDEs, and cost-optimality analysis. He collaborates with Prof. Dirk Praetorius and contributes to projects funded by the Austrian Science Fund (FWF). Previously, he was a PhD student (2020–2024) and taught courses in numerical mathematics and scientific programming. His work bridges theoretical advancements in adaptive algorithms with practical computational efficiency, addressing challenges in nonsymmetric and semilinear PDEs. Education: PhD in Technical Mathematics, TU Wien (2024), supervised by Dirk Praetorius MSc in Technical Mathematics, TU Wien (2020), supervised by Winfried Auzinger Research Interests: His interdisciplinary work centers on developing adaptive FEM strategies for cost-optimal solutions to PDEs. Key areas include: Contractive iterative solvers for nonlinear systems Goal-oriented error estimation for targeted accuracy Quasi-optimal computational cost in adaptive algorithms His methods prioritize minimizing computational resources while maintaining solution fidelity, with applications to elliptic and semilinear PDEs. Awards: 2025 Study Prize (ÖMG) for PhD thesis Grants & Funding: FWF Projects P33216 and P28367 Vienna School of Mathematics membership (2020–present) Labs/Teams: Core member of the Numerics of PDEs research group, part of TU Wien's ASC unit. Active in collaborative projects with international conferences and workshops.

• Tomography
• Inverse Problems
• Medical Imaging
• +3 more

Peter Elbau is a Senior Lecturer (Privatdozent) in the Faculty of Mathematics at [University Name, if known]. His research focuses on mathematical imaging techniques, particularly in tomography and inverse problems, with applications in medical and biomedical imaging. He is actively involved in projects such as the "Tomography across the scales" initiative, aiming to develop quantitative imaging methods from molecular to astronomical scales. His primary research interests include the mathematical foundations of tomographic imaging, inverse scattering problems, and quantitative parameter reconstruction in optical coherence tomography (OCT) and photoacoustic imaging. He explores topics such as motion detection in diffraction tomography, curvature flows on surfaces, and the development of algorithms for medical diagnostics and material characterization. Elbau leads the research project "Tomography across the scales - Quantitative optical imaging from single molecules to stars," funded from 2018 to 2026. This project highlights his role in bridging fundamental mathematical research with practical applications in imaging technologies. His work often involves cross-disciplinary teams focusing on biomedical and material imaging challenges.

Bernhard KerblView profile

Researcher

• Real-time graphics
• High-performance rendering
• Virtual Reality (VR)
• +3 more

Bernhard Kerbl is a Researcher and Teaching Assistant at the Institute of Computer Graphics and Vision, Technical University of Graz (TU Graz). He holds a Master’s degree in Software Engineering and Economics. His research focuses on parallel and distributed processing, with special emphasis on adaptive rendering and GPU optimization under Prof. Dieter Schmalstieg and Dr. Markus Steinberger. His interests include real-time graphics, high-performance rendering, and Virtual Reality (VR). He contributes to teaching by organizing lectures on computer graphics. His recent work involves publications in areas like adaptive radiance caching and distributed rendering systems. Collaborations include projects with industry and academic partners, though specific grants or lab affiliations are not detailed in the provided texts.

• Optimizing Compilers
• Program Analysis
• Embedded Systems
• +4 more

Jens Knoop is a Full Professor at TU Wien, leading the Department of Information Systems Engineering (E194) and the Research Unit Compilers and Languages (E194-05). His roles include Head of Institute for Information Systems Engineering and membership in the Curriculum Commission for Informatics. He specializes in compiler design, program analysis, and embedded systems, with a focus on worst-case execution time (WCET) analysis and formal methods. His research interests span optimizing compilers, programming languages, and real-time computing. Notable contributions include the Platin tool suite for WCET analysis and contributions to the T-CREST project on time-predictable multi-core architectures. He has authored and edited multiple influential publications, including proceedings of international conferences such as Code Generation and Optimization (CGO) and ARCS. Professor Knoop has supervised numerous theses, including works on effect systems in Haskell, mutation testing in Rust, and robotic systems. He has received the Most Influential PLDI Paper Award (2002) for foundational work in compiler optimization.