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.
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.
Dr. Regino Criado is Full Professor of Applied Mathematics at Rey Juan Carlos University (URJC), where he has held academic positions since June 2000. He currently serves as Academic Director of the Data, Complex Networks and Cybersecurity Sciences Institute (since March 2017) and was elected to the Academia Europaea in May 2023. His career spans European research projects (ESPRIT II/III) and interdisciplinary collaborations at the intersection of mathematics, computer science, and cybersecurity. His research focuses on Complex Networks , including hyper-networks, multiplex networks, and mesoscale structures, with applications to cybersecurity, intentional risk management, and synchronization phenomena. Key innovations include: A game theory-based intentional risk model integrating accessibility, anonymity, and value metrics Hybrid network mining algorithms for credit card fraud detection PageRank extensions to multiplex networks Framework for discrete resilience analysis in technological systems His work on the 2014 Physics Reports monograph The structure and dynamics of multilayer networks (3,500+ citations) established foundational concepts in multilayer network theory. Current research explores linguistic pattern analysis through multilayer hypergraphs for automatic text summarization. Member of Academia Europaea (2023) Chaos Journal Best Paper Award (2011) Academic Entrepeneurs Prize (2002) EUROPA-1992 Prize (1992) As director of the DCNC Institute (2017-present) and BBVA-URJC Chair (2017-2018), he has led major academic-industry collaborations. His 180+ publications (6,500+ citations) demonstrate sustained impact across network science, applied mathematics, and cybersecurity.
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.
Cesar Ranero is a Research Professor at ICREA (Catalan Institution for Research and Advanced Studies) and the Head of the Barcelona Center for Subsurface Imaging (BCSI) at the Institute of Marine Sciences (ICM), Barcelona, Spain. His expertise spans tectonics, earthquakes, and subduction zone processes, with a focus on integrating seismic imaging and field experiments. He leads multi-national projects and has coordinated over 11 chief scientist cruises, contributing to major breakthroughs in understanding continental rifting and seafloor spreading mechanisms. Education: BSc (1987) from the Basque Country University, PhD in Earth Sciences (1989) from the Jaume Almera Institute (CSIC, Barcelona). Awards include the 'Ciutat de Barcelona' Prize (2019) and AGU Fellowship (2018). He pioneered novel subsurface imaging techniques and secured over €11.5 million in funding, including EU and industry grants. Supervised 10 PhD, 8 MSc students, and 20+ postdocs, managing a dynamic team of ~20 researchers annually at BCSI. Research focuses on subduction zone dynamics, rifted margins, and seismic methods. Key projects include the Costa Rica Seismogenic Potential (CRISP) drilling initiative and the Tyrrhenian TIME proposal. His work bridges geophysics, tectonics, and marine geology, addressing fundamental questions about plate boundary interactions and seismic hazard assessment.
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
Gerald Quentin Maguire Jr. is a Professor (emeritus) at KTH Royal Institute of Technology, Sweden, specializing in Computer Science and Communication Systems. He holds a Ph.D. in Computer Science from the University of Utah and a B.A. in Physics from Indiana University of Pennsylvania. His academic roles include Professor of Computer Communication at KTH since 1994, and prior positions at Columbia University and the U.S. National Science Foundation. He has contributed to fields like data communications, medical imaging, and mobile computing. Education: Ph.D. in Computer Science, University of Utah, 1983 M.S. in Computer Science, University of Utah, 1981 B.A. in Physics (magna cum laude), Indiana University of Pennsylvania, 1975 Research Interests: Focuses on network protocols, mobile computing, medical imaging integration, and high-performance computing. His work includes cognitive radio systems, GPU-centric networking, and CT/PET fusion for medical diagnostics. Awards: IEEE Fellow (2013) Teacher of the Year (2006/2007, KTH) Giovanni DiChiro Award (1997) Multiple honors in medical imaging and network research Advising & Grants: Supervised 8 doctoral students and over 75 master's students. Authored 5 books and numerous papers, with over 200 invited lectures globally. His research has been supported by grants from Swedish and international funding bodies. Labs & Teams: Formerly led the Computer Communication Systems Lab (CCSlab) at KTH and collaborated with Karolinska Institutet on medical imaging projects.
Valero Mateo is a Full Professor at the Department of Computer Architecture, Technical University of Catalonia (UPC), and Director of the Barcelona Supercomputing Center (BSC). He holds leadership roles in high-performance computing and computer architecture research, directing national and international projects like the BSC and CIRI. His career includes chairing departments, leading research institutes, and advising Intel's Microprocessor Lab. He has been recognized with prestigious awards, including the Eckert-Mauchly Award and multiple honorary doctorates. His research focuses on high-performance computing systems, parallel processing, and supercomputing infrastructure. Recent honors include the 2024 Vanguardia Innovation and Science Award and the inaugural Barceloní Prize. Affiliations: BSC (since 2004), UPC (since 1974), CEPBA (1990–1995). Education: Engineer in Telecommunications, UPC (1974). Research: Pioneering work in supercomputing architectures, energy-efficient computing, and parallel systems. Awards: Over 60 international awards, including ACM and IEEE Fellowships. Grants: ERC Advanced Grants, Spanish and European research funding. Labs/Teams: Leads BSC, collaborates with global institutions like NASA and IBM.
Antonio Vallecillo is a Full Professor at the University of Málaga, leading the ATENEA research group focused on Software Modeling and Analysis. He has held key academic and administrative roles, including Vice-President of the Spanish Society on Informatics (SCIE), President of SISTEDES (Spanish Society on Software Engineering), and coordinator of the Computer Science and Information Technologies area at the Spanish Research Agency (AEI). His work spans standardization activities in AENOR, ISO, and ITU-T, where he edited three international standards on Open Distributed Processing. Research interests include Model-Driven Engineering, Software Quality, Enterprise Architectures, and Model Transformations. He has over 120 publications in top venues, secured €2M+ in research funding, and pioneered conferences like STAF and ICMT. His contributions to open-source tools for model transformation validation and international standards underscore his impact. Awards include Best Paper distinctions and the 10-Year Most Influential Paper Award. Academic leadership roles include Vice-President of Postgraduate Studies at the University of Málaga and Director of University IT systems. He actively participates in editorial boards (SoSym, JOT) and international conferences as PC Chair and keynote speaker.
Jiri Wiedermann is a Professor of Computer Science at Charles University and has served as Director of the Institute of Computer Science at the Academy of Sciences of the Czech Republic since 2000. His academic journey includes an Assoc. Prof. position at Charles University (2000) and degrees from Comenius University (RNDr., M.Sc.) and Czechoslovak Academy of Sciences (CSc., DrSc.). Education : DrSc. in Computer Science (Comenius University, Bratislava, 1993) CSc. (equiv. to PhD) in Computer Science (Czechoslovak Academy of Sciences, Prague, 1980) RNDr. and M.Sc. in Computer Science (Comenius University, Bratislava, 1974) His research spans Theoretical Computer Science , focusing on computational complexity, neurocomputing, and non-standard computing. He explores embodied cognition, mirror neurons, and autopoietic automata, bridging neural models with algorithmic frameworks. The 15 most recent publications highlight his work on interactive computation, fuzzy Turing machines, evolving artificial living systems, and cognitive architectures. Key trends include machine learning inspired by biological systems , computational limits of cognition , and formal models of neural processes . Scientific Awards : Member of Academia Europaea (since 2006) Member of the Czech Learned Society (since 2003) Board of Directors, ERCIM (since 1997) Leadership roles in EATCS (Vicepresident 1997-2002)
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.
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.
Siddiqi Shafaq is a Researcher at TU Graz's Institute of Human-Centred Computing, holding a Dr.techn. (technical doctorate), BSc, and M.Sc. Her work bridges computer science and human-centric applications, focusing on machine learning, data science, and education technology. She contributes to interdisciplinary research, including smart surveillance systems, cloud computing security, and IoT applications. Her educational background includes advanced technical degrees, though specific institutions are not detailed. Research interests span machine learning interpretability, data cleaning frameworks, outlier detection in non-IID datasets, and educational paradigms like U-Learning. Her publications highlight innovation in declarative ML systems (SystemDS), ontology-driven opinion mining, and CPU-GPU optimization. Her articles collectively explore trends in scalable data science pipelines, ethical AI practices, and real-world deployment challenges. Notable work includes analyzing internet addiction's academic impacts and designing trusted cloud platforms. No awards or grants are explicitly listed, though her active publication history suggests ongoing research engagement. Shafaq is affiliated with TU Graz's Institute of Human-Centred Computing, contributing to both research and teaching activities (via unspecified courses). No student advisees or lab affiliations are mentioned in the provided data.
Dan Alistarh is a Professor at the Institute of Science and Technology Austria (IST Austria) and leads the Deep Algorithms and Systems Lab (DASLab). His research focuses on efficient algorithms and systems for machine learning, including distributed optimization, sparse and quantized neural networks, and scalable training/inference techniques. He holds a PhD from École Polytechnique Fédérale de Lausanne (EPFL) and has held positions at MIT, Microsoft Research, and ETH Zurich. Research interests: Optimization for data analysis, parallel and distributed optimization, efficient machine learning algorithms, and distributed systems. Collaborations include work on optimization under uncertainty with Immanuel Bomze, Radu Bot, and others. Publications span top venues like NeurIPS, ICML, and DISC, with notable contributions in model compression (e.g., GPTQ, SparseGPT), communication-efficient distributed training, and concurrency algorithms. Awards include ERC grants and best paper awards. He advises a team of PhD students and postdocs, and his lab's tools are widely used (e.g., GitHub repositories). His work has been adopted in industry (e.g., OpenAI, Neural Magic).
Vladimir Kolmogorov is a Professor at the Institute of Science and Technology Austria (IST Austria), leading the Kolmogorov Group focused on Discrete Optimization. He previously held positions as Assistant Professor at IST Austria (2011–2014), Lecturer at University College London (2005–2011), and Associate Researcher at Microsoft Research (2003–2005). His research spans algorithm development for graphical models, combinatorial optimization, and applications in computer vision. Education: M.S. in Applied Mathematics and Physics from the Moscow Institute of Physics and Technology, and Ph.D. in Computer Science from Cornell University (2003). Research interests include complexity classifications, algorithm design for discrete optimization problems (e.g., max-flow, min-cost matching), and applications in computer vision. Notable contributions include the 'Boykov-Kolmogorov' max-flow algorithm and 'Blossom V' for minimum cost perfect matching. Honors include the ERC Consolidator Grant (2014–2019), Koenderink Prize (2012), and best paper awards at CVPR and ECCV. His work on optimization algorithms and theoretical complexity has significantly impacted computer vision and combinatorial optimization fields. Advising and grants: Supervised multiple PhD students and postdocs, with current advisees including Martin Dvořák and Pavel Arkhipov. His team explores inference in graphical models, combinatorial optimization, and discrete optimization theory.
