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Dr. Rajkumar Buyya is a Redmond Barry Distinguished Professor at the University of Melbourne and Founder & CEO of Manjrasoft , a spin-off commercializing cloud innovations. He has held visiting roles at Imperial College London , University of Birmingham , and Tsinghua University . Research Interests : His work spans Cloud Computing , Edge Computing , Grid Systems , and Energy-Efficient Computing , focusing on utility-driven resource allocation, simulation tools, and scalable IoT application frameworks. He pioneered the CloudSim toolkit and Aneka Cloud technologies. Scientific Awards : IEEE Fellow (2015), Web of Science Highly Cited Researcher (2016-2021) Khwarizmi International Award (2020), Scopus Researcher of the Year (2017) Frost & Sullivan New Product Innovation Award (2010), IEEE TCSC Medal (2009) Impact : Authored over 850 publications, including the widely adopted textbook Mastering Cloud Computing . Graduated 54 PhD students now in leadership roles at institutions like Newcastle University and companies such as IBM , Google , and Amazon . His research has driven global adoption of cloud/edge technologies in 50+ countries.

• Cluster computing
• Grid computing
• Software systems
• +7 more

F. Richard Yu is a Professor at the School of Information Technology , Carleton University , Canada, since 2016. He served as Assistant/Associate Professor at the same institution from 2006 to 2015. His academic work spans machine learning, blockchain, autonomous vehicles, and network security. Ph.D., Electrical Engineering, University of British Columbia (2003) M.A.Sc., Computer Engineering, Beijing University of Posts & Telecomm. (1998) B.A.Sc., Electrical Engineering, Dalian University of Technology (1995) His research focuses on machine learning , blockchain , autonomous vehicles , network security , and mobile wireless networks . Trends in his publications include deep reinforcement learning for computation offloading , blockchain applications in edge computing , and network optimization for IoT and 5G systems . Highly Cited Researcher (2019-2023), Clarivate Electronics and Electrical Engineering Leader in Canada (2023), Research.com Fellow of Canadian Academy of Engineering (CAE) (2021), Engineering Institute of Canada (EIC) (2019), IEEE (2017), and IET (2016) Best Paper Awards: IEEE ICC (2022), IEEE GLOBECOM (2020), IEEE VTC (2017), IEEE TAOS (2012), IEEE TrustCom (2009) Research Achievement Award, Carleton University (2021, 2012) Early Researcher Award (2011), Ontario; Leadership Opportunity Fund Award (2009), Canada Foundation for Innovation His work has resulted in 800+ papers , 30 patents , and 48,000+ citations (H-index 107), with grants including the 2009 Canada Foundation for Innovation award.

• Machine learning and artificial intelligence
• Connected and autonomous vehicles
• Blockchain and distributed ledger technology
• +2 more

Dragi Kimovski is a Habilitated Assistant Professor in Distributed Systems at Klagenfurt University, Austria, focusing on Edge Computing and AI. He previously held roles at the University of Innsbruck and the University of Information Science and Technology in Macedonia. His research spans Edge/Fog/Cloud computing, multi-objective optimization, and high-performance computing. He has coordinated major projects like 6GContinuum and KärtnerFog, and led initiatives such as DataCloud and ASPIDE. His teaching includes courses on Distributed Computing, Cloud Computing, and IoT. He is the co-creator of the Carinthian Computing Continuum and maintains a blog on Edge AI World. His work emphasizes sustainable and efficient computing solutions for emerging technologies. Education: Not explicitly listed in the provided text. Research Interests: Edge Computing, Fog Computing, Cloud Computing, Multi-objective Optimization, High-Performance Computing, AI in Distributed Systems. His work addresses challenges in resource management, latency reduction, and scalability across heterogeneous environments, with applications in healthcare, IoT, and 6G networks. Projects: 6GContinuum (Coordinator): Focuses on AI services over 6G networks. KärtnerFog (Scientific Coordinator): Develops adaptive Fog infrastructures over 5G. DataCloud (WP5 Leader): Manages Big Data pipelines on the Computing Continuum. ASPIDE (Scientific Coordinator): Advances exascale programming models for data processing. Teaching: Klagenfurt University: Courses include Distributed Computing, IoT, Cloud Computing, and Advanced Programming. University of Innsbruck: Taught Advanced Parallel and Distributed Systems. University of Information Science and Technology: Courses in High-Performance Computing and Network Architectures. Labs/Teams: Co-created the Carinthian Computing Continuum, an automated SDN testbed for Edge computing research. Active in interdisciplinary teams addressing extreme data processing and sustainable computing.

• Edge Computing
• Fog Computing
• Cloud Computing
• +4 more

Thomas Werner Pusztai is a Researcher at the Department of Distributed Systems, TU Wien. His work focuses on cloud-edge continuum systems, serverless computing, and service-level objective (SLO) management. He contributes to projects like RapidREC, TEADAL, and the EU-funded RAINBOW initiative. His research spans distributed scheduling algorithms, edge-cloud resource allocation, and SLO-aware middleware frameworks like Polaris and HyperDrive. Education: Completed a Diploma in Computer Science at TU Wien with a thesis on Model-based design and architecture of fog computing applications (2019). Active in academic conferences, presenting at IEEE/ACM Edge Computing, Cloud, and Fog/Edge events. Research interests include edge computing, cloud-native systems, IoT applications, and optimizing SLO compliance through novel scheduling techniques. His work emphasizes practical frameworks for real-world distributed systems challenges. Projects include developing HyperDrive for serverless function scheduling in 3D edge-cloud spaces, Polaris for SLO-aware microservices orchestration, and SLO Script for complex elasticity-driven SLO implementations.

• Distributed Systems
• Cloud Computing
• Edge Computing
• +4 more

Peter Mandl is an Associate Professor affiliated with the Institute for Computer Science Education at the University of Klagenfurt. His research focuses on Geoinformatics, Artificial Intelligence, Environmental Research, Remote Sensing, and Computer Simulation. He explores topics such as socio-ecological systems, spatial agent-based modeling, land use change, and urban and regional analysis. His work integrates interdisciplinary approaches, combining GIS technology with environmental policy, social sciences, and engineering. Key research interests include the application of geospatial tools for sustainable land use planning, renewable energy assessment, and modeling complex geographic systems. He has contributed to studies on forest fuel markets, satellite image interpretation, and fog phenomena in climate research. His publications emphasize spatial decision support systems, agent-based simulation frameworks, and the development of open geoinformatics platforms like RadWeb Mittelkärnten. His articles demonstrate a consistent focus on bridging theoretical modeling with practical applications, often using agent-based methods to analyze environmental, economic, and social systems. While no scientific awards are explicitly mentioned, his contributions to geoinformatics education and research are evident through his extensive publication record and teaching roles. Collaborative projects and grants are not detailed here, but his work suggests involvement in interdisciplinary teams addressing environmental and urban challenges. Labs and teams associated with his research are not explicitly listed, though his affiliations imply participation in geoinformatics and environmental science groups at the University of Klagenfurt.

• Geoinformatics
• Artificial Intelligence
• Environmental Research
• +7 more

Dr. Richard Yu is a Professor at the School of Information Technology, Carleton University, Canada, with academic roles spanning since 2006. His research bridges machine learning, blockchain, and wireless networks, focusing on emerging technologies like vehicular systems and edge computing. Ph.D. in Electrical Engineering (UBC, Canada) M.A.Sc. in Computer Engineering (Beijing University of Posts & Telecomm.) B.A.Sc. in Electrical Engineering (Dalian University of Technology) His research explores machine learning and blockchain integration in connected vehicles , mobile networks , and IoT , emphasizing security and resource optimization . His work often employs deep reinforcement learning to address challenges in distributed systems. Recent publications focus on blockchain-enabled edge computing , vehicular networks , and IoT optimization , with methodologies centered on reinforcement learning , interference alignment , and secure transmission . 2023: Electronics and Electrical Engineering Leader, Research.com 2022: IEEE ICC Best Paper Award 2021: Fellow, Canadian Academy of Engineering 2020: IEEE GLOBECOM Best Paper Award 2019: IEEE TCGCC Distinguished Service Award 2017: IEEE VTC Best Paper Award 2017: IEEE Fellow 2016: IET Fellow 2011: Ontario Early Researcher Award His grants include the Canada Foundation for Innovation’s Leadership Opportunity Fund Award (2009). Collaborative work with students and colleagues underpins his contributions to wireless systems and blockchain.

• Machine learning and artificial intelligence
• Connected and autonomous vehicles
• Blockchain and distributed ledger technology
• +2 more

Wolfgang Kastner is a Full Professor at the Department of Automation Systems, Faculty of Informatics, Vienna University of Technology (TU Wien). His research focuses on Distributed Automation, Industry 4.0, Smart Grids, IoT, and Cybersecurity in Industrial Systems. He is affiliated with TU Wien and actively contributes to projects funded by institutions like the Austrian Research Promotion Agency (FFG) and TÜV Austria. His work spans safety, security, and integration challenges in IT/OT convergence. Research interests include Industrial Automation, Cyber-physical Systems, and IoT applications. He leads projects such as the TÜV AUSTRIA Security in Industry Research Lab and collaborates on initiatives like FORA (Fog Computing for Robotics) and DiCYCLE (Digitalization in Construction). His research addresses energy efficiency, fault detection, and semantic integration in industrial and building automation systems. Key projects include: Unleashing Sector-coupling Flexibility (2023–2027) Contextual Deep Learning for Predictive Analytics (2023) Semantics-based Explanation of Cyber-physical Systems (2023–2025) His contributions to standards like Asset Administration Shell (AAS) and AutomationML (AML) highlight his role in bridging theoretical and applied cybersecurity and safety engineering.

• Distributed Automation
• Industry 4.0
• Smart Grids
• +8 more

Alireza Furutanpey is a University Assistant (PreDoc Researcher) at TU Wien's Distributed Systems Group within the Institute of Information Systems Engineering, holding a Master's degree with distinction. His academic role combines research in distributed systems with teaching responsibilities for core computer science courses. His educational background includes: Bachelor of Science (BSc) Master of Science (Dipl.-Ing.) with distinction Furutanpey's research centers on Edge Computing and Edge Intelligence, specializing in Distributed Inference, Neural Data Compression, and AI-Systems integration. He pioneers techniques for neural feature compression in satellite/edge environments and develops frameworks for federated learning orchestration under communication constraints. His work bridges theoretical AI with practical system implementation, focusing on resource-constrained scenarios where bandwidth and computational efficiency are critical. Analysis of his 15+ publications reveals dominant trends in neural compression for distributed systems (60%), federated learning optimization (25%), and serverless edge frameworks (15%). Key contributions include solving satellite downlink bottlenecks through feature compression and enabling adaptive inference in heterogeneous edge networks, with methodologies increasingly incorporating generative modeling and robustness against adversarial attacks. Scientific Awards: None documented in available sources. He actively supervises master's theses, guiding students on adversarial machine learning, neural compression, and image retrieval systems. His research is supported through major projects: AloTwin (2023-2025) focusing on edge intelligence, INTEND (2024-2026) on industrial IoT, and TEADAL (2022-2025) on federated learning. He serves as a reviewer for 15+ IEEE/ACM venues including IEEE Transactions on Mobile Computing and ICDCS. Furutanpey operates within TU Wien's Distributed Systems Group, which specializes in edge-cloud continuum research. The team develops tools like faas-sim for serverless edge simulation and explores quantum-classical hybrid architectures, maintaining strong industry collaborations in industrial IoT and satellite communications.

• Edge Computing
• Edge Intelligence
• Distributed Inference
• +3 more

Xiaoming Fu is a Full Professor of Computer Science at the University of Göttingen, Germany, and Founding Director of the Sino-German Institute of Social Computing. He earned a Ph.D. from Tsinghua University (2000) and has held academic positions at TU Berlin (2000-2002) and the University of Göttingen since 2002. His research spans mobile computing, social computing, cloud computing, big data analysis, and networked systems, with a focus on (mobile) social networks, Internet of Things, and software-defined networking. Education : Ph.D. (2000) from Tsinghua University, Beijing, China. Key Positions : Founding Director, Sino-German Institute of Social Computing (2015-present); University Professor and Head of Computer Networks Group (2007-present); Assistant Professor (2002-2007); DAAD Visiting Professor at Columbia University (2008-2009); Fulbright Scholar at UCLA (2009). Editorial Leadership : Editor-in-Chief of the Journal of Social Computing and ACM Transactions on Social Computing; served on editorial boards of IEEE Network, IEEE Communications Magazine, and others. Research Leadership : Principal Investigator for EU FP6-ENABLE, FP7-GreenICN, H2020 COSAFE, and MobileCloud projects; coordinator of EU H2020 ICN2020 and CleanSky projects. Leadership in Professional Organizations : Vice Chair of IEEE Communications Society Technical Committee on Computer Communications (2010-2012); Chair of IEEE Communications Society and Internet Society Internet Technical Committee (2011-2013); founding co-chair of IEEE Vehicular Technology Society Germany Chapter. Honors and Awards : IEEE Fellow (2022), ACM Distinguished Member (2021), Member of acatech (2024), Fellow of the Institute of Engineering and Technology (2017), and more.

• Mobile Computing
• Social Computing
• Cloud Computing
• +7 more

Pantelis Frangoudis is a PostDoctoral Researcher at the Distributed Systems Group of the Vienna University of Technology since 2019. His academic journey includes a Ph.D. in Computer Science (2012), M.Sc. (2005), and B.Sc. (2003) from the Department of Informatics, Athens University of Economics and Business (AUEB) , Greece. His research spans Edge Computing , IoT , Network Softwarization , Federated Learning , and Wireless Networking , focusing on adaptive systems and security. Education B.Sc. in Computer Science (2003), AUEB M.Sc. in Computer Science (2005), AUEB Ph.D. in Computer Science (2012), AUEB His research explores Edge Computing Continuum systems, with emphasis on QoS-aware orchestration , serverless edge deployment , and self-adaptive IoT services . Recent work addresses federated learning for 6G , WebAssembly for edge serverless , and dynamic resource allocation in heterogeneous environments. Key projects include AloTwin (2023–2025), INTEND (2024–2026), and EDENSPACE (2019–2022). His publications (2025–2020) cover machine learning for 5G/6G , MEC application orchestration , and IoT security , with a focus on distributed systems and edge-cloud collaboration . Scientific Awards ERCIM Alain Bensoussan Post-Doctoral Fellowship He has supervised multiple diploma theses at TU Vienna, including topics like serverless edge computing , traffic light AI optimization , and vertical farming IoT systems . His collaborations with institutions like EURECOM (France) and IRISA/INRIA (France) reflect a global academic footprint.

• Mobile/Wireless Networking
• Edge Computing
• Network Softwarization
• +4 more

Wilfried Steiner is an Associate Professor at the Institute for Computer Engineering within the Faculty of Informatics at TU Wien. His research focuses on fault tolerance, safety-critical systems, distributed algorithms, and formal analysis in cyber-physical systems. He actively teaches courses and supervises master's theses, with a bachelor thesis course scheduled for the 2025 winter semester. Steiner's research centers on dependable communication systems, particularly time-triggered architectures for safety-critical applications. He has pioneered solutions for fault containment, system startup, and Byzantine faults in distributed real-time systems. His work extends to fog computing for industrial IoT through the FORA project (2017-2021), addressing resource constraints in automotive and industrial environments while maintaining deterministic behavior. His publication timeline reveals consistent innovation: early foundational work (2002-2007) established protocols for fault-tolerant time-triggered communication, evolving toward fog computing platforms (2020-2021) for industrial IoT. Recent publications emphasize automotive applications (TTEthernet/AUTOSAR) and IoT channel synchronization, demonstrating sustained relevance in real-time system design. Steiner has supervised nine master's theses between 2018-2024, including Walser (2024) on time-aware container virtualization, Reisinger (2022) on distributed clock synchronization, and Schorn (2021) on automotive fail-operational strategies. His research is supported by projects like FORA, which developed fog computing solutions for industrial IoT constraints. As a core member of the Cyber-Physical Systems research group (E191-01), Steiner contributes to TU Wien's leadership in safety-critical embedded systems, focusing on integration of computing, networking, and physical processes for automotive and industrial applications.

• Fault Tolerance
• Safety-Critical Systems
• Distributed Algorithms
• +4 more

Stefan Schulte is an Associate Professor at TU Wien's Faculty of Informatics, holding a habilitation in Computer Science. His roles include Vice Dean of Academic Affairs for Business Informatics. He earned a diploma in economics, bachelor's in Computer Science from the University of Oldenburg, and master’s from the University of Newcastle. He completed his PhD at TU Darmstadt and habilitation at TU Wien. His research focuses on data engineering, elastic computing, IoT, QoS/QoE, fog computing, and blockchain for data provenance. He leads projects like SIMPLI-CITY and CREMA, coordinating EU-funded initiatives. Education: Diploma in Economics (Oldenburg), BSc Computer Science (Oldenburg), MSc Information Technology (Newcastle), PhD (TU Darmstadt, 2010), habilitation (TU Wien, 2018). Research Interests: Data stream processing in IoT and smart systems Elastic computing frameworks for cloud/fog environments Blockchain applications for verification and interoperability QoS optimization in distributed systems Smart mobility and manufacturing systems Publications: Over 100 refereed papers in top venues like IEEE Transactions on Services Computing and VLDB. Recent work emphasizes fog computing architectures and cross-blockchain solutions. Awards: Multiple best paper awards (ESOCC 2020, Blockchain-2020), teaching recognition, and prestigious awards for student theses (OCG Incentive Award, Vienna City Awards). Grants/Advising: Coordinated EU projects SIMPLI-CITY and CREMA, supervised over 30 theses. Active in PhD supervision for Cyber-Physical Production Systems. Labs/Teams: Director of TU Wien's Distributed Systems Group (DSG), leading Fog Computing and Blockchain research initiatives.

• Data Engineering
• Elastic Computing
• Internet of Things (IoT)
• +6 more

Christos Tsigkanos is an Assistant Professor at the University of Athens, Department of Aerospace Science and Technology, leading the Space Software Group. He holds a PhD from Politecnico di Milano (2017) and a Habilitation (2022). Previously, he was a post-doctoral researcher at TU Vienna and a Lise Meitner Fellow at the Austrian Science Foundation. His research focuses on software systems engineering, dependable systems, and space software, emphasizing formal methods and cyber-physical systems. Education: PhD in Software Engineering, Politecnico di Milano, 2017 Habilitation, 2022 Research Interests: Christos explores the intersection of software engineering and systems engineering, with a focus on dependability, formal methods, and space software systems. His work addresses challenges in temporal logics for specifications, runtime verification for IoT and edge systems, and model-driven engineering for reactive systems. He emphasizes practical applications in aerospace and robotics. Recent Articles: Recent work includes formal verification techniques for space software architectures, temporal logic applications in robotics, and scalable analysis of reactive systems. These contributions bridge theoretical formal methods with real-world software engineering challenges. Awards: ACM SIGSOFT Distinguished Paper Award (2020) Grants & Projects: RUNVERSPACE (PI, SNSF) ERMIS Constellation In-Orbit Validation (ESA Collaboration) RV4THINGS (Hellenic Foundation for Research) Labs/Teams: Leads the Space Software Group at the University of Athens, focusing on verified space software and cyber-physical systems. Collaborates with the University of Bern on space mission software assurance.

• Software Engineering
• Systems Engineering
• Dependable Systems
• +4 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.

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

Athman Bouguettaya is a Professor at the School of Computer Science, University of Sydney, Australia. He previously served as Head of School at RMIT University and the University of Sydney. His academic journey includes tenured roles at Virginia Tech (USA) and senior positions at Queensland University of Technology. He is an IEEE Fellow, ACM Distinguished Scientist, and recipient of the IEEE TCSVC Research Innovation Award. Education: PhD in Computer Science from the University of Colorado at Boulder (1992). Research focuses on service computing, IoT, cloud computing, and drone services. Notable contributions include frameworks for drone delivery systems, energy-efficient IoT services, and trust management in crowdsourced systems. His work spans 280+ publications in top venues like IEEE TKDE and ACM TWeb. Awards include WISE Fellow (2019), ACM Distinguished Speaker (2019), and IEEE Computer Society Distinguished Visitor (2020). Grants include major funding from ARC, NSF, Qatar NPRP, and industry partnerships with HP/Sun Microsystems. He directed the E-Commerce and E-Government Research Lab (ECEG) and chairs editorial boards for IEEE Transactions on Services Computing and others. Labs/Teams: ECEG Lab, leadership roles in CSIRO ICT Centre, and advisory roles in conferences like ICSOC and WISE.

• Service Computing
• Internet of Things (IoT)
• Cloud Computing
• +4 more