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Juraj HromkovičView profile

Professor

• Theoretical Computer Science
• Algorithms
• Complexity Theory
• +6 more

Juraj Hromkovič is a Full Professor of Computer Science at the Swiss Federal Institute of Technology (ETH Zurich) , holding this position since 2004. His academic career spans multiple institutions, including Professorships at Christian Albrechts University in Kiel (1994-1997), RWTH Aachen (1997-2003), and earlier roles at Comenius University and the University of Paderborn. Education : 1977–1982: Studied Computer Science at Comenius University, Bratislava 1982: Dr. rer. nat. (PhD equivalent) from Comenius University 1986: CSc (Ph.D.) in Theoretical Cybernetics 1990: Dr. Sc. in Mathematics and Physics Research Interests focus on Theoretical Computer Science , particularly Algorithms , Complexity Theory , and Communication Protocols . His work explores Randomized Algorithms , Approximation Techniques , and Automata Theory , with notable contributions to understanding exponential gaps in computational models and optimizing information dissemination in networks. His publications span books, journal articles, and conference papers addressing foundational and applied aspects of computing. Scientific Awards include membership in the Slovak Academy of Sciences (2001) and two awards from the Slovak Literature Foundation for Scientific Literature (2002, 2004). He has supervised 11 PhD dissertations and one habilitation, demonstrating his commitment to academic mentorship.

• Distributed Databases
• Object-Oriented Databases
• Internet Databases
• +9 more

Erich Neuhold is a Professor of Computer Science at the University of Vienna and Darmstadt University of Technology. He holds honorary professorships at several institutions, including the University of Guiyang and the New Jersey Institute of Technology. His career spans over five decades, with roles as Director of the Fraunhofer Institute for Integrated Publication and Information Systems (IPSI) and professorships at multiple universities globally. Education: Erich Neuhold earned a Dipl.-Ing. (M.S.) in Electronics and a Dr.-techn. (PhD) in Mathematics and Computer Science from the Technical University of Vienna. He holds special honors in his academic career, including Fellowships from IEEE and the Gesellschaft für Informatik. Research Interests: His work focuses on distributed databases, object-oriented systems, internet databases, information retrieval, semantic web, interoperability, and applications in digital libraries, e-science, and e-government. He pioneered advancements in transaction models, multimedia databases, and semantic integration frameworks. Publications: Over 200 papers and four books, with recent contributions including retrospectives on computing history and foundational work in supercomputing architectures. His articles reflect deep engagement with historical and future trends in computer science. Awards: Recognitions include the Meritorious Service Award from IEEE, medals from academic institutions, and honorary professorships worldwide. Grants & Labs: Led projects like the POREL distributed database system and contributed to initiatives like the EU’s FRESCO e-science cockpit. His work spans academic-industrial collaborations, with budget leadership at IPSI (€10M/year). Labs/Teams: Co-founded the Fraunhofer IPSI and directed research teams in Austria, Germany, and internationally, emphasizing interdisciplinary collaboration in information systems.

Adithya VadapalliView profile

Assistant Professor

• Cryptography
• Secure Multi-Party Computation
• Oblivious RAM
• +3 more

Adithya Vadapalli is an Assistant Professor at the Department of Computer Science and Engineering (IIT Kanpur, India). His research focuses on constructing systems that prevent data leaks through cryptographic methods, with broader applications in secure computation and privacy preservation. Education: Ph.D. in Computer Science from Indiana University Bloomington. Prior Role: Postdoctoral Fellow at the University of Waterloo (CrySP group). His research interests include: Secure Multi-Party Computation (SMPC) Oblivious RAM (ORAM) design Metadata protection techniques Privacy-preserving machine learning Recent publications highlight advancements in cryptographic primitives like distributed point functions, bandwidth-efficient distributed ORAM, and round-efficient 3-party MPC for dynamic data structures. These works span theoretical foundations and practical implementations. Currently, no scientific awards or student records are explicitly listed in the provided materials.

Tirado FranciscoView profile

Professor

• Power Aware Computing
• Heterogeneous Computing
• Applications optimization
• +4 more

Francisco Tirado is a Full Professor of Computer Architecture at Complutense University of Madrid since 1986. He has held leadership roles including Vice-Chancellor for Research (2012-2015), Dean of the Faculty of Physics (1994-2002), and Director of the Complutense Supercomputing Center (2002-2007). He is a founding member of the Spanish Society for Computer Science (SCIE) and Spanish Society for Computer Architecture (SARTECO). His research focuses on power-aware computing, heterogeneous systems, bioinformatics, and hardware design automation. He has authored over 242 publications and supervised 15 PhD theses. His professional service includes chairing 138 international conferences and serving on numerous committees for EUROMICRO, IEEE, and national research agencies. Education: No explicit details provided, but has been active at Complutense University since 1978. Affiliations: Member of COSCE Executive Board (2012), IEEE Senior Member (2005), and EUROMICRO Board (1991-2004). Research Interests: - Optimizing energy efficiency in high-performance computing systems - Design of heterogeneous architectures and accelerators - Bioinformatics applications through hardware/software co-design - Parallel programming models for emerging architectures - Automation tools for FPGA and embedded systems development Conference Contributions: Played multiple roles (General Chair, Program Chair) for major events like ParCo, HPCA, and EUROMICRO PDP conferences. Delivered 64 keynote/plenary lectures globally. Scientific Awards: Doctor 'Honoris Causa' from universities in Spain, Paraguay, and Peru 2013 National Computer Science Award IEEE Senior Membership Advising: Supervised 15 PhD students. Active in technology transfer contracts with industry. Labs/Teams: Founder and leader of the ArTeCS research group at Complutense University, specializing in computer architecture and high-performance computing innovations.

Monika HenzingerView profile

Professor

• Combinatorial Optimization
• Dynamic Optimization
• Parallel and Distributed Optimization
• +5 more

Monika Henzinger is a Full Professor of Computer Science at the Institute of Science and Technology Austria (IST Austria) and Deputy Speaker of the Vienna Graduate School on Computational Optimization. She holds a PhD from Princeton University and has held positions at Cornell University, Digital Equipment Corporation, Google, EPFL, and the University of Vienna. Her research focuses on combinatorial algorithms, dynamic optimization, and efficient graph algorithms. She leads a group at IST Austria exploring algorithm design for dynamic environments, privacy-preserving algorithms, and practical implementations of theoretical results. Research Interests: Combinatorial algorithms (especially graphs), dynamic algorithms, approximation algorithms, algorithmic game theory, and privacy-preserving computation. Her work includes breakthroughs in decremental graph algorithms, submodular optimization, and computational advertising. Collaborations: Works with Vladimir Kolmogorov, Nysret Musliu, Günther Raidl (Combinatorial Optimization), Birgit Rudloff (Dynamic Optimization), and Dan Alistarh (Parallel/Distributed Optimization). Awards: Wittgenstein Award (2021), ERC Advanced Grants (2021, 2014), ACM Fellow (2016), and numerous others listed in her CV. Grants & Labs: Principal investigator on an ERC Advanced Grant for graph algorithms. Her team includes PhD students (e.g., Bardiya Aryanfard, Antoine El-Hayek) and postdocs focused on algorithmic challenges in dynamic systems.

• High-Performance Computing
• Big Data Processing
• Performance Portability
• +3 more

Enes Bajrovic is a researcher affiliated with the Faculty of Computer Science, focusing on high-performance computing (HPC), big data processing, and performance portability. His work spans task-based parallelism, runtime systems, and optimization frameworks for heterogeneous architectures. He has contributed to major European projects like PEPPHER and AutoTune, which aim to advance HPC software tools and autotuning methodologies. His research emphasizes practical applications of parallel computing in domains such as mobile networks and scientific simulations. Education: Dipl.-Ing. Dr.techn., BSc in Computer Science His research interests include developing frameworks for compute- and data-intensive applications, leveraging technologies like Kubernetes, OpenCL, and Intel Xeon Phi coprocessors. He has authored numerous peer-reviewed publications on topics such as pipeline patterns, autotuning algorithms, and hybrid execution models. His work bridges theoretical advancements in parallel computing with real-world software engineering challenges. Bajrovic has collaborated on projects funded by the European Commission’s FP7 program, contributing to deliverables like runtime systems, tuning frameworks, and benchmarking tools. His research also addresses the integration of big data processing with HPC, particularly in telecommunications and distributed computing environments.

Mher SafaryanView profile

Researcher

• Optimization theory and algorithms
• Machine learning
• Federated learning
• +7 more

Dr. Mher Safaryan is a postdoctoral researcher at the Institute of Science and Technology Austria (ISTA), affiliated with Prof. Dan Alistarh's research group since 2022. Previously, he held postdoctoral positions at King Abdullah University of Science and Technology (KAUST) from 2019-2022 and served as a research technician there from 2016-2019. He earned his Ph.D. in Mathematics from Yerevan State University in 2018 under Prof. Grigori Karagulyan's supervision. Education: Ph.D. in Mathematics (2018, YSU) Past Affiliations: KAUST (2016-2022), Neural Magic/Red Hat (industrial secondment) His research focuses on optimization theory and algorithms for machine learning , particularly in developing communication/computation/memory-efficient methods for large-scale training and federated learning. Key contributions include LDAdam (low-dimensional gradient statistics optimization), GradSkip (accelerated local gradient methods), and Unified Scaling Laws for compressed representations. He has published in top venues like NeurIPS, ICML, ICLR, TMLR, and The Journal of Geometric Analysis. Scientific Awards: Marie Skłodowska-Curie Fellowship (MSCA COFUND IST-BRIDGE) His work bridges machine learning optimization with mathematical foundations from his earlier research in real harmonic analysis. Current collaborations include Prof. Dan Alistarh (ISTA), Dr. Alexandre Marques (Neural Magic), and Prof. Peter Richtárik (KAUST).

• Algorithms
• Sparse Matrices
• Parallel Computing
• +3 more

Robert Ernstbrunner is a researcher affiliated with the Faculty of Computer Science , contributing to algorithm development and parallel computing. His work focuses on low-rank approximations and fault-tolerant strategies in linear algebra methods. Research Interests: His research spans computational efficiency, numerical linear algebra, and fault tolerance in high-performance computing environments. Key areas include sparse matrix operations and resilience mechanisms for iterative algorithms. Publications: He has published two peer-reviewed papers: (1) a 2022 study on precision-cost trade-offs in low-rank matrix approximations, and (2) a 2020 framework for node-failure resilience in iterative linear algebra methods. Academic Activities: Robert has presented at international conferences, including the 2022 IEEE IPDPS and the 2020 FTXS workshop.

Kazuo IwamaView profile

Professor

• Stable Matchings
• Boolean Satisfiability
• Auction algorithms
• +13 more

Kazuo Iwama is a Professor at the School of Informatics, Kyoto University, where he has been employed since 1997. He previously served as a Professor at Kyushu University's Department of Information Science (1992–1997) and held various academic positions, including Associate Professor and Visiting Associate Professor, at institutions such as Kyoto Sangyo University and UC Berkeley's Computer Science Division. Education Ph.D., Electrical Engineering, Kyoto University (1980) M.E., Electrical Engineering, Kyoto University (1975) B.E., Electrical Engineering, Kyoto University (1980) His research spans theoretical computer science, with a focus on algorithms, computational complexity, and quantum computing. Key areas include stable matchings, approximation algorithms, Boolean satisfiability, and quantum network coding. Scientific Awards 2008 Honorary Doctorate from University of Latvia 2005 Member, Science Council of Japan

Michael AffenzellerView profile

Professor

• Genetic Programming
• Symbolic Regression
• Evolutionary Algorithms
• +6 more

Michael Affenzeller is a Professor at the University of Applied Sciences Upper Austria, leading the HEAL AIST Center of Excellence for Smart Production with a focus on Digital Transformation. His research spans Genetic Programming, Symbolic Regression, and Evolutionary Algorithms, with applications in optimization, AI, and manufacturing automation. He has authored over 400 publications and led major projects such as HCAI (Human-Centered AI) and HEAL, emphasizing interdisciplinary collaboration. Research interests include developing advanced algorithms for dynamic optimization, prescriptive analytics, and federated learning in industrial contexts. He has contributed to projects like LOISI (Logistics Optimization in Steel Industries) and SimGenOpt2, addressing challenges in production planning and workforce optimization. Key collaborations involve institutions in Austria and beyond, focusing on smart manufacturing, logistics, and AI integration. His work bridges theoretical advancements with real-world applications, driving innovation in energy systems, crane scheduling, and predictive maintenance. Grants and projects include funding from FWF (doc.funds.connect) and Upper Austrian initiatives, emphasizing doctoral training and industry partnerships. He actively participates in conferences such as EUROCAST and PPSN, contributing to algorithmic advancements and computational theory.

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.

• Membrane Computing
• Theoretical Computer Science
• Formal Languages
• +3 more

Marion Oswald is an External Lecturer at the Technische Universität Wien (TU Wien), affiliated with the Institute of Logic and Computation under the Faculty of Informatics. Her research focuses on membrane computing, P systems, spiking neural P systems, formal languages, and computational models. She has contributed to projects such as the Austrian Science Fund (FWF)-funded initiative on the theoretical foundations of membrane systems (2004–2007). Oswald holds a Diplom-Ingenieur (2001) and a Dr.techn. (2003) from TU Wien. She has supervised theses including work on tissue P systems and applications of membrane systems in distributed systems. Her educational background includes advanced studies in molecular computations and formal languages. Research interests extend to computational complexity, neural networks, and discrete mathematics. Oswald has taught courses such as 'Theoretical Computer Science' and 'Fundamentals of Computer Science for Geodesy and Geomatics Engineering.' Key contributions include advancing computational models like spiking neural P systems, exploring control mechanisms in P systems, and investigating undecidability in array-based computational frameworks. Her work bridges theoretical computer science with practical applications in neuroscience and distributed systems modeling.

• Distributed Systems
• Computer Science
• Networking
• +3 more

Ao.Univ.Prof. Dipl.-Ing. Dr.techn. Markus Peschl is a full professor affiliated with the Institute of Distributed Systems at TU Wien. His research focuses on distributed systems, networking, and related computational paradigms. He holds academic titles including Austrian University Professor (Ao.Univ.Prof.) and Doctor of Technical Sciences (Dr.techn.) . Contact details include his university email and TISS profile.

• Distributed Systems
• Service Platforms
• Energy-Aware Computing
• +1 more

Margret Steinbuch is a Researcher in Distributed Systems at the Vienna University of Technology. Her work focuses on federated data systems, energy-aware computing, and performance optimization for heterogeneous architectures. Her research explores trustworthy data lakes, service platform engineering, and scalable computing solutions for modern distributed environments. Steinbuch has contributed to multiple European Commission projects including INDENICA (engineering virtual service platforms) and COIN (enterprise interoperability). Her articles consistently address optimization challenges in distributed and parallel computing systems. She coordinates laboratory resources and infrastructure for distributed systems research while collaborating on international technology initiatives.

• High Performance Computing
• MPI Programming
• Parallel Algorithms
• +2 more

Ioannis Vardas is a Researcher in Parallel Computing at TU Wien's Faculty of Informatics. His work focuses on optimizing high-performance computing systems through advanced process mapping, MPI programming, and performance analysis tools. Key research areas: Topology-aware process mapping for HPC MPI library development and optimization Performance profiling of parallel applications Resource allocation in hierarchical architectures Energy-efficient parallel computing He contributes to projects improving MPI performance tools and develops methods for efficient resource utilization in supercomputing environments.