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Matthias JanetschekView profile

Associate Professor

• Computer Science
• Cybersecurity
• Distributed Systems
• +5 more

Matthias Janetschek holds the position of Associate Professor at the Management Center Innsbruck (MCI), Austria, since September 2020. Previously, he served as a Lecturer at MCI (2018–2020) and was a Co-Founder/Senior Developer at Felix Solution UG (2013–2015). He earned a PhD in Computer Science from the University of Innsbruck (2011–2019), alongside earlier degrees in Computer Science (BSc 2002–2007, MSc 2007–2011). His research focuses on distributed systems, workflow management, cybersecurity, and IoT , with notable contributions to scientific workflow execution on cloud/manycore architectures and AR/VR applications in education. He has supervised over 18 bachelor/master theses addressing topics like IoT security, reinforcement learning, and edge computing. Teaching responsibilities include courses such as Distributed Systems , Virtual Reality , and Computer Architecture at MCI. He has also completed further training in online education tools (e.g., Sakai, Adobe Connect) and corporate communication. His publications span journals like Multimodal Technologies and Interaction and conference proceedings on workflow systems, cloud computing, and AR usability. Current work emphasizes large-scale IoT security assessments and edge computing optimizations.

• Computer Architecture
• Compilers
• Programming Languages
• +4 more

Andreas Krall is an Associate Professor in the Department of Software Technology at TU Wien's Faculty of Informatics. He holds roles as Curriculum Coordinator for the Bachelor Informatics and Bachelor Software and Information Engineering programs, and serves as a Substitute Member of the Curriculum Commission for Informatics. His research focuses on compiler design, architecture description languages (e.g., VADL), and formal methods for ensuring correctness in compiler-processor co-design. Key research areas include computer architecture, compiler verification, embedded systems, and the development of tools for processor simulation and optimization. Krall has led projects such as 'Correct Compilers for Correct Processors' (2010–2015) and contributed to the CACAO JVM project. He has published extensively on topics like instruction selection, abstract state machines (CASM), and SSA-based optimizations. Notable awards include the Heinz Zemanek Preis (1987). His work spans over 30 years, with contributions to both academic research and industry-relevant tools like the VADL architecture description framework. Krall has advised numerous students in topics ranging from compiler backends to garbage collection algorithms.

• Automated Software Verification
• Formal Methods
• Model Checking
• +7 more

Georg Weissenbacher is a Full Professor in the Institute of Logic and Computation at TU Wien, leading the Formal Methods in Systems Engineering group. His research focuses on automated software verification, formal methods, and concurrency bug analysis. He holds a DPhil from Oxford and has held positions at Princeton and ETH Zurich. Education: TU Wien (since 2010), Postdoctoral Researcher at Princeton University (2010–2012), PhD from Oxford University (2008–2010), Research Assistant at ETH Zürich (2005–2010), Master's at TU Graz (until 2003). Research Interests: Automated software verification, formal methods, model checking, concurrency bug detection, logic and automated reasoning, symbolic simulation, and test case generation. His work addresses challenges like Heisenbugs in concurrent systems and robustness verification of neural networks. Grants & Projects: Lead projects such as AutoTest (Vienna Science Fund), LogiCS-Scholarships (2017–2025), and contributions to the National Research Network 'Rigorous Systems Engineering' (FWF). Active in the FWF-funded doctoral college 'Automated Reasoning' (2025). Advising: Supervised over 20 PhD and master's students, including notable works on Heisenbugs, mutation testing, and neural network verification. Current advisees include Thomas Hader and Sarah Sallinger. Labs & Teams: FORSYTE Group at TU Wien, collaborating on formal methods and automated reasoning. Engaged in international conferences like CAV and FMCAD as program chair/co-chair.

• Compilers
• Programming Languages
• Computer Architecture
• +3 more

Benedikt Lukas Huber serves as a PreDoc Researcher at TU Wien's Faculty of Informatics within the Compilers and Languages research group (Institute E194-05), located at Argentinierstrasse 8, Room EA0402. His primary affiliation centers on compiler technologies and system architecture research. His research spans Compilers , Programming Languages , and Computer Architecture , with specialized focus on architecture description languages and compiler optimization techniques like software pipelining. Recent work demonstrates sustained innovation in formal system modeling and performance-critical code generation. Publication analysis reveals consistent contributions to compiler infrastructure, particularly through the Vienna Architecture Description Language (2024) and foundational software pipelining research (2008), highlighting expertise in bridging hardware constraints with high-level language design. No scientific awards or fellowships were documented in available sources. Information regarding student advising, research grants, or leadership roles remains unspecified beyond his core research group affiliation. He operates within TU Wien's Compilers and Languages research ecosystem, contributing to compiler design and system architecture initiatives under the Institute of Engineering Mathematics and Computing Science.

Petter E. BjørstadView profile

Professor

• Numerical analysis
• Domain decomposition
• Elliptic PDE
• +4 more

Petter E. Bjørstad is a Professor of Computer Science and Mathematics at the University of Bergen, Norway, where he has served as Head of the Department of Informatics since 2010. Previously, he was Director of the Bergen Center for Computational Science (2000-2010) and Professor in both the Department of Mathematics (2006-2010) and Department of Informatics (1985-2005). He also held a position as Professor of Mathematics at the University of Minnesota during 1996-1997 on unpaid leave from Bergen. Dr. Bjørstad earned his PhD in Computer Science from Stanford University in 1980, following which he completed a postdoctoral fellowship at the Courant Institute of Mathematical Sciences at New York University. Before entering academia, he worked as a Principal Engineer at Det Norske Veritas from 1981-1985. Dr. Bjørstad's research focuses on numerical analysis and high-performance computing, with particular expertise in domain decomposition methods, parallel algorithms for elliptic partial differential equations, and scientific computing. His work bridges theoretical mathematics with practical computational challenges, especially in industrial applications. He has led significant research projects including 'Multiscale Domain Decomposition: Algorithms and Analysis' (2010-2014), funded by the Research Council of Norway and the University of Bergen. His publication record demonstrates consistent contributions to the field of numerical methods and parallel computing over several decades. The research trends show a strong focus on developing efficient algorithms for solving partial differential equations through domain decomposition techniques, with applications spanning structural analysis, reservoir simulation, semiconductor device modeling, and other industrial contexts. His work increasingly emphasizes practical implementation on modern parallel architectures including SIMD and MIMD systems. Large number of research grants from Norway and the European Union Dr. Bjørstad has been actively involved in mentoring students and collaborating with industry through projects like the Europort effort, where industrial codes were ported to parallel computing platforms. His laboratory for parallel computing (Parallab) has been instrumental in advancing practical applications of high-performance computing since its establishment in 1985 with Europe's first 64-processor Intel hypercube. The lab has evolved to include multiple MIMD machines including an Intel Paragon, Parsytec GC/Power-Plus, and DEC α-cluster. As Head of the Department of Informatics, Dr. Bjørstad leads one of Norway's premier computing research units with expertise spanning theoretical computer science, numerical methods, and practical applications in various scientific domains. His leadership has helped establish Bergen as a significant center for computational science in Europe.

Esparza JavierView profile

Professor

• Algorithms and tools for the design and verification of reactive and distributed systems
• Verification of systems with infinitely many states
• Software Model Checking
• +7 more

Javier Esparza is a Professor at the Technische Universität München, holding the Chair of Foundations of Software Reliability and Theoretical Computer Science since 2007. Prior to this, he held chairs at the University of Stuttgart (2003-2007) and the University of Edinburgh (2001-2003), along with academic positions dating back to 1990. Education: M.S. in Theoretical Physics (1987, University of Zaragoza), Ph.D. in Computer Science (1990, University of Zaragoza), and Habilitation in Computer Science (1994, University of Hildesheim). His research focuses on formal verification, distributed systems, and software reliability, particularly through algorithms for software model checking, logic and automata theory, and analysis of probabilistic systems. His work has been supported by numerous grants from the German Research Council (DFG), British Engineering and Physical Sciences Research Council (EPSRC), and the Humboldt Foundation. Scientific Awards: Doctor honoris causa from Masaryk University (2009), TeachInf Awards for best Bachelor and Master courses (2009, 2010), TU München Diploma for excellent teaching (2011), Member of Academia Europaea (2011), and Dissertation Prize from the University of Zaragoza (1990). Esparza has supervised over 15 PhD students, including Dr. Stefan Schwoon, Dr. Claus Schröter, and Dr. Michael Luttenberger, and collaborated on research projects with institutions across Europe and the UK.

Val TannenView profile

Professor

• Database Theory
• Programming Language Theory
• Data Provenance
• +5 more

Val Tannen is a Professor in the Department of Computer and Information Science (CIS) at the University of Pennsylvania, holding appointments since 1987. He has undertaken numerous visiting roles, including at Simons Institute (2023), EPFL (2020, 2011-2012), NUS (2019), and institutions in Greece, France, and elsewhere. Education: Polytechnic Institute of Bucharest (Engineer Diploma, 1977) MIT (PhD in Applied Mathematics/Computer Science, 1983-1987) His research spans database theory, programming language theory, logic, and applications to bioinformatics. Key contributions include provenance frameworks and complex object modeling , impacting data integration, uncertainty management, and systematic biology. Notable awards include ACM Fellowship , Mendelzon Test-of-Time Award , and NSF Presidential Young Investigator . His work has been disseminated through 30+ conference program committee roles and editorial contributions. Scientific Awards: 10 years Mendelzon Test-of-Time Award ACM Fellow 20 years Test-of-Time Award NSF Presidential Young Investigator

Li KeqinView profile

Professor

• Computer Networking
• Heterogeneous Computing Systems
• Computer Architectures and Systems
• +6 more

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.

• Automated Reasoning
• Systolic Computations
• Multiprecision Arithmetic
• +3 more

Tudor Jebelean is a full professor at the Research Institute for Symbolic Computation (RISC) within Johannes Kepler University (JKU), located in Linz, Austria. His primary affiliation is with RISC, where he leads research in automated reasoning, symbolic computation, and algorithm design. Roles: A.Univ.-Prof. (Universitätsprofessor) at RISC, JKU Research Focus: Automated reasoning, systolic computations, multiprecision arithmetic, and formal methods. Jebelean's work centers on advancing theorem proving systems like Theorema , which integrates computation and deduction for natural-style mathematics. He develops algorithms for sorting, data structure manipulation, and formal verification, often using combinatorial and logic-based techniques. His contributions include the design of systolic architectures for arithmetic operations and the synthesis of algorithms through mechanical proving. Publications highlight his research on automated prover systems, certification of sorting algorithms, and symbolic computation tools. He collaborates extensively with researchers like Isabela Dramnesc and Sorin Stratulat on algorithm synthesis and formal verification. His research bridges theoretical foundations with practical applications in computer science and mathematics education.

• High-Performance Computing
• Parallel Programming
• GPU Computing
• +3 more

assoz. Prof. Dipl.-Ing. Dr. Peter Thoman is an Associate Professor in the Department of Computer Science at the University of Innsbruck. His work focuses on high-performance computing, parallel programming models, and GPU-accelerated systems. He leads research in areas such as SYCL standard implementations, distributed computing optimizations, and energy-efficient algorithms for exascale applications. His research interests include task-based parallelism, heterogeneous computing architectures, and scalable runtime systems. Notable contributions include the Celerity API for accelerator clusters and the LIGATE drug discovery platform. He is affiliated with the University of Innsbruck’s technical research groups and collaborates on projects like the AllScale framework. Dr. Thoman’s teaching includes courses on parallel programming and high-performance computing systems. He is a member of the Department’s leadership team under Prof. Thomas Fahringer.

Thomas FahringerView profile

Professor

• Parallel Computing
• Distributed Systems
• High-Performance Computing (HPC)
• +4 more

Thomas Fahringer is a full Professor and Head of the Distributed and Parallel Systems Group at the University of Innsbruck's Institute of Computer Science. His research focuses on parallel computing, distributed systems, and high-performance computing (HPC), with particular emphasis on GPU acceleration, cloud/edge computing, and serverless architectures. He leads interdisciplinary projects involving scientific workflows, resource management systems, and exascale computing solutions. Key research areas include: Design of high-level APIs for accelerator clusters (e.g., Celerity-RSim) Optimization of IoT and LoRa networks using machine learning Scalable key-value stores for geo-distributed systems Workflow scheduling in edge-cloud continuum environments Recent work emphasizes automation of deployments, energy-efficient transmission policies, and fault-tolerant orchestration of serverless functions. He actively participates in community initiatives like the Workflows Community Summit, driving advancements in scientific workflows and HPC ecosystems. His lab develops frameworks such as Apollo and AllScale, targeting exascale computing and distributed runtime systems.

Erich SchikutaView profile

Associate Professor

• Cloud Computing
• Information and Database Systems
• Parallel and Distributed Computing
• +3 more

Erich Schikuta is an associate professor at the University of Vienna's Faculty of Computer Science and heads the Research Group Workflow Systems and Technology. He has held multiple administrative roles, including Vice Dean and Curricular Commission Head. His research focuses on Cloud Computing, Parallel/Distributed Systems, Neural Networks, and Database Systems, with over 200 peer-reviewed publications. Education: Studied Computer Science, Business Informatics, and Mathematics at the University of Technology Vienna and University of Vienna. Holds titles including Dipl.-Ing., Dr., and Berufstitel Universitätsprofessor (2009). Research interests emphasize Utility Computing, Cloud Resource Optimization, and Neural Network Simulation. Notable contributions include ranking 25th globally in Cloud Computing productivity and developing frameworks like N2Sky for neural network-as-a-service. Key awards include the 2011 Best Paper Award and 2010 Best Teacher Award. Active in international collaborations, he serves as a European Commission evaluator (FP5-FP7/H2020) and chairs program committees. Labs/Teams: Leads the Research Group Workflow Systems and Technology. Involved in projects like BIG-Business (Grid Infrastructure) and 'Änderung in kollab.Prozessen' (2011-2016).

Stefan WagnerView profile

Professor

• Evolutionary Computation
• Optimization
• Genetic Algorithms
• +4 more

Stefan Wagner serves as a Professor at the University of Applied Sciences Upper Austria (FH OOE), based at the Research Center Hagenberg Center of Excellence for Smart Production. His academic affiliation resides within the Department of Production and Operations Management under the institution's ICT focal area. Wagner holds the title FH-Prof. DI Dr. and actively serves as Principal Investigator (PI) on multiple research projects including ENPro (Energy Neutral Production) and JRZ adaptOp (Josef Ressel Center for Adaptive Optimization), driving innovation in optimization and smart manufacturing systems. Wagner's research expertise centers on Evolutionary Computation and Optimization , with specialized focus on Genetic Algorithms, Heuristic Optimization, and Dynamic Optimization. As lead developer of HeuristicLab —an open-source optimization environment—he bridges theoretical advances with industrial applications in Symbolic Regression, Production Scheduling, and Energy-Efficient Manufacturing. His work addresses complex challenges in logistics, crane scheduling, and energy-neutral production through evolutionary techniques. Recent publications (2025) reveal a pronounced trend toward distributed and dynamic optimization frameworks. Key themes include diversity management in changing environments, containerization for scalable evolutionary computation, and hybrid cooperative approaches for symbolic regression. Applications span container terminal logistics, energy-neutral manufacturing, and robust unloading bay optimization, demonstrating strong industry-oriented problem-solving. Wagner received the FH OÖ Researcher Award in 2019 for exceptional contributions. He has secured funding for 9 research projects including ENPro (2025-2028) and SMART UNLOAD, frequently serving as PI or Co-PI. His projects tackle production optimization, workforce planning, and energy efficiency in Upper Austrian manufacturing. With 4 supervised students and extensive community engagement through EvoSoft at GECCO and EUROCAST peer review, he actively shapes the evolutionary computation landscape. Leading the HeuristicLab project, Wagner collaborates with industry partners through the Center Hagenberg research team to develop simulation and optimization tools for adaptive scheduling. His current work in the ENPro project targets energy-neutral production via modeling and optimization, positioning him at the forefront of sustainable manufacturing innovation in industrial settings.

• Formal Methods
• Parallel and Distributed Computing
• Symbolic Computation
• +3 more

Wolfgang Schreiner is an A.Univ.-Prof. (Associate University Professor) at the Research Institute for Symbolic Computation (RISC), Johannes Kepler University Linz, Austria. His research focuses on formal methods, parallel and distributed computing, and symbolic computation. He leads projects in automated reasoning, programming language semantics, and educational software tools. His work emphasizes practical applications of formal methods, including the development of tools like RISCAL for model checking and the RISC ProgramExplorer for program reasoning. He collaborates on interdisciplinary projects, such as analyzing queueing systems using probabilistic model checking and designing grid computing frameworks for medical applications. Key research interests include semantics-based language design, theorem proving, and educational technology. He has authored textbooks like *Concrete Abstractions* and *Thinking Programs*, emphasizing foundational concepts in computer science. His contributions span theoretical advancements and practical implementations, with notable work in distributed systems, formal verification, and computational logic.

Majid SalimibeniView profile

Research Fellow

• High Performance Computing
• Parallel Computing
• Message Passing in Large-scale HPC systems
• +6 more

Majid Salimibeni is a PostDoc Researcher and Research Fellow at Vienna University of Technology (TU Wien) , affiliated with the Parallel Computing research unit. He previously held a Postdoc position at the Department of Computer Science at the University of Salerno, Italy (2024), and has been a visiting researcher at TU Wien (2023). Currently based in Vienna, Austria, his work focuses on High Performance Computing (HPC) and its interdisciplinary applications. Education: Ph.D. in Computer Science, University of Salerno, Italy (2020–2024) M.Sc. in Computer Engineering (Software), Shiraz University, Iran (2017–2020) B.Sc. in Computer Engineering (Software), University of Birjand, Iran (2012–2016) Salimibeni's research explores High Performance and Parallel Computing , with a focus on optimizing GPU communication via NCCL , improving energy efficiency in heterogeneous computing environments , and enhancing MPI collective algorithms for large-scale systems. His work bridges HPC infrastructure with emerging applications in Distributed Deep Learning and AI . Recent publications highlight his expertise in GPU frequency scaling , NCCL profiling , and process arrival pattern analysis to improve distributed system performance. These works appear at top conferences like IPDPS , Cluster Computing , and ASHPC . Scientific Awards: Best Paper Award, Bench 2022 Salimibeni contributes to academic committees as a program committee member for IEEE ICPP 2025, ISC 2025, and BigHPC 2024, and serves on artifact evaluation committees for ASPLOS and CF conferences.