جست‌وجوی استاد و پژوهشگر

• Cloud Computing
• Distributed Systems
• IoT Service Composition
• +۳ مورد دیگر

Dr. Abdessalam Elhabbash is a Lecturer in Distributed Systems at the Department of Computing and Communications, Lancaster University. His research focuses on IoT service composition, cloud computing, and self-adaptive systems. He is affiliated with the Lancaster Intelligent, Robotic and Autonomous Systems (LIRA) Centre and leads research groups such as LIRA - Environmental Modelling and LIRA - Extreme Environments. His work emphasizes ontological architectures for system composition, cloud migration optimization, and AI-driven IoT frameworks like the IoT Whisperer and TRANSITIVE. Elhabbash advises PhD student Qianhui Lin. He is contactable at a.elhabbash@lancaster.ac.uk. Research interests include: IoT service composition using large language models (LLMs) Multi-cloud performance optimization and pricing strategies Autonomous system design through ontological frameworks Predictive maintenance in Industry 4.0 environments Recent publications highlight advancements in cloud migration tools (PricingTheCloud), edge computing architectures (HolonCraft), and self-aware system development. His work bridges theoretical foundations with practical applications in smart home automation and industrial IoT. Labs/Teams: Active member of LIRA's environmental and extreme environment groups, focusing on resilient distributed systems in challenging conditions.

Ming Xiaoمشاهده پروفایل

دانشیار

• Wireless Communications
• Network Coding
• Machine Learning
• +۱۰ مورد دیگر

Ming Xiao is an Associate Professor in the Division of Information Science and Engineering at KTH Royal Institute of Technology's School of Electrical Engineering and Computer Science (EECS). He is affiliated with the Digital Futures Faculty and leads research in wireless communications, machine learning, and network coding. His work focuses on 6G networks, distributed learning, and secure communications. Affiliations: KTH EECS, Digital Futures, Swedish Research Council, EU Horizon Europe projects Roles: Editor for IEEE Transactions on Wireless Communications, TPC Co-Chair for VTC Fall Research Interests: Dr. Xiao's expertise spans wireless communication systems (e.g., mmWave, NOMA), network coding, machine learning applications in communications, and energy-efficient distributed systems. He has pioneered work on intelligent reconfigurable surfaces (RIS), federated learning in edge computing, and integrated sensing-communications (ISAC). Projects: Ongoing EU-funded projects include ASCENT (autonomous vehicular networks) and COVER (unmanned aerial vehicles for emergency response). Past projects include 6G channel coding and intelligent energy management in smart communities. Grants: Over 12 active grants from VR, EU Horizon Europe, FORMAS, STINT, and VINNOVA Awards: IEEE Vehicular Technologies Society Best Paper Award (2023), World Top 2% Researcher (2020–2023), Highly Cited Researcher in Computer Science/Engineering. Labs/Teams: Leads the KTH Digital Futures initiative, collaborates with RISE Research Institutes, and manages a team of 12 PhD students/postdocs focusing on 6G, distributed ML, and secure IoT.

Jaime Llorcaمشاهده پروفایل

استاد پژوهشی

• Network Algorithms
• Network Optimization
• Distributed Control
• +۵ مورد دیگر

Jaime Llorca is a Research Professor at the New York University (NYU) Tandon School of Engineering's Electrical and Computer Engineering Department. He holds affiliations with NYU WIRELESS, a research center focused on 6G and beyond. His work bridges network algorithms, optimization, and distributed control with applications in edge computing, cloud networks, and content delivery. Prior roles include Senior Research Scientist at Nokia Bell Labs and positions at Alcatel-Lucent Bell Labs and the University of Maryland's Center for Networking of Infrastructure Sensors. Education: M.S. and Ph.D. in Electrical and Computer Engineering from the University of Maryland, College Park (MD). Research Focus: Llorca pioneers advancements in network-coded caching, distributed cloud control, and edge-cloud integration. Notable contributions include 'cache-aided coded multicasting' and 'cloud-network flow' frameworks. His work addresses latency constraints, resource allocation, and service orchestration in next-generation networks. Key Achievements: Over 100 peer-reviewed publications and 20 patents. Awarded the 2007 IEEE Sensors Best Paper Award, 2016 IEEE ICC Best Paper Award, and the 2015 Jimmy H.C. Lin Award for Innovation. Co-developed foundational technologies for content delivery and distributed cloud networks. Advising & Grants: Advises on distributed computing networks and edge-cloud systems. His research is supported by grants focused on 6G, network optimization, and IoT integration. Collaborates closely with NYU WIRELESS on projects like the Vineyard Digital Twin initiative leveraging UAV imaging. Labs & Teams: Active member of NYU WIRELESS, advancing 6G, mmWave/terahertz networks, and cross-layer network programmability. Leads teams exploring morphable networks and end-to-end service orchestration.

• Computer Networks
• Edge Computing
• Internet of Things (IoT)
• +۵ مورد دیگر

Paolo Bellavista is a Full Professor of Distributed and Mobile Systems at the Department of Computer Science - Science and Engineering, Alma Mater Studiorum – University of Bologna. His research focuses on edge computing, federated learning, IoT, digital twins, and blockchain applications. With over 140 journal articles and 200+ conference papers, his work appears in top venues such as ACM Computing Surveys and IEEE Transactions. He serves as Editor-in-Chief of the MDPI Computers Journal and holds editorial roles in IEEE Communications Surveys&Tutorials and ACM Computing Surveys. His contributions span network optimization, cybersecurity, and smart cities, with notable achievements in citation metrics (h-index 46 on Google Scholar). Research interests include distributed systems, vehicular networks, AI-driven security, and QoS-aware edge infrastructures. He has organized major conferences like IEEE Mobile Cloud and ACM ICDCN. Current projects explore federated learning unlearning, digital twin entanglement, and blockchain-based data spaces. His work bridges theoretical foundations with real-world deployments in smart manufacturing and healthcare. Editorial Roles : MDPI Computers (Editor-in-Chief), IEEE Communications Surveys&Tutorials (Associate Editor), ACM Computing Surveys (Editor) Conference Leadership : Technical Program Chair for IEEE Mobile Cloud 2015, General Co-Chair for SCNS 2018 Key Contributions : Over 140 journal papers, 15 special issues as guest editor, and 200+ conference publications His lab develops middleware for edge-cloud continuum applications and collaborates internationally on projects like InAbled Cities. Office hours are held weekly at the University of Bologna’s DISI department.

• Distributed Software Systems
• Network Function Virtualization
• Formal Verification
• +۳ مورد دیگر

Patrick Eugster is a full professor at the Università della Svizzera italiana (USI) and leads the Software Systems (SWYSTEMS) group within the Computer Systems Institute . He has held academic positions at Purdue University, TU Darmstadt, and MIT as a visiting faculty. His research focuses on distributed software systems , addressing challenges in consistency, efficiency, and security in decentralized environments. Current affiliation: USI Faculty of Informatics Prior affiliations: Purdue University (2005-2016), TU Darmstadt (2014-2017), MIT (2012/2013) Research Interests Distributed Systems : Investigating reliable failure detection, deterministic data paths for 6G, and hybrid synchronous/asynchronous architectures. Network Innovation : Optimizing TCAM encoding, analyzing microbursts, and developing quantum network protocols. Security & Verification : Creating confidentiality-preserving mechanisms and formal verification approaches for distributed software. Scientific Contributions 2025: Best paper at TACAS on Horn clause validation 2025: IFIP Jean-Claude Laprie Award for dependable computing 2024: Key papers at IEEE Network, ACM PLDI, and IEEE INFOCOM Funding & Collaborations Swiss National Science Foundation grants #200021_197353 and #200021_192121 EU Horizon Europe MSCA staff exchange project CloudStars Industry partners: Cisco, Amazon AWS, Facebook Research, SAP, Northrop Grumman Cybersecurity Research Consortium Labs & Teams Directs the SWYSTEMS group, which includes postdocs like Sina Darabi and Shamiek Mangipudi, PhD students such as Anita Buckley and Jérôme Graf, and alumni who have become faculty at institutions like Télécom Paris and University of Southern California.

Siris Vasiliosمشاهده پروفایل

استاد

• Resource Management in Networks
• Distributed Ledger Technologies (DLTs)
• Blockchains and IoT Security
• +۳ مورد دیگر

Professor Siris Vasilios holds the position of full Professor at the Department of Informatics, Athens University of Economics and Business (AUEB). Previously, he served as Assistant and Associate Professor at AUEB (2009–2020) and the University of Crete (2002–2009). His expertise spans resource management in networks, blockchain-based IoT security, and future communication systems. He has published over 150 papers in top venues like IEEE INFOCOM and ACM Mobicom, and holds three patents in wireless resource management. Education: Diploma in Physics (1990), National and Kapodistrian University of Athens M.S. in Computer Science (1992), Northeastern University, Boston, USA Ph.D. in Computer Science (1998), University of Crete Research Interests: His work focuses on trusted communication in IoT , leveraging blockchain technologies for secure systems. Key areas include distributed ledger applications, energy-efficient network protocols, and satellite-terrestrial integration. He emphasizes combining theoretical methods with practical system implementations. Awards & Recognition: He has coordinated EU-funded projects (e.g., SOFIE) and served as Technical Program Chair for IEEE WoWMoM 2018 and IQ2S 2015. His research has been recognized through grants from Greek governmental and industry partners. Grants & Projects: Principal Investigator for multiple EU research projects Lead on Greek national and industry-funded initiatives Contributed to the SOFIE project addressing IoT security via interledger technologies Labs & Teams: Active in the Department of Informatics' research groups, focusing on experimental systems like Dedalus for wireless maritime networking and blockchain-based IoT prototypes.

Kwangsung Ohمشاهده پروفایل

استادیار

• Computer Science
• Data Analytics
• Cloud Computing
• +۳ مورد دیگر

Kwangsung Oh is an Assistant Professor in the Department of Computer Science at the University of Nebraska at Omaha's College of Information Science & Technology. His research focuses on GPU-based image reconstruction, cloud computing optimization, and deep learning for software evolution. Contact: kwangsungoh@unomaha.edu . Research Areas GPU Acceleration for Biomedical Imaging Geo-distributed Data Analytics Serverless Computing Optimization Machine Learning in Software Engineering Recent publications demonstrate expertise in structured illumination microscopy algorithms, cloud storage policy frameworks, and deep learning-driven code inspection tools. His work bridges computational biology applications with distributed systems infrastructure.

• Cloud Computing
• Computer Networking
• Machine Learning
• +۱ مورد دیگر

Xiaoqian (Tiffany) Zhang is an Assistant Professor in the Department of Computer Science at the University of Nebraska at Omaha (UNO) College of Information Science & Technology. Her work focuses on cloud computing, computer networking, and cybersecurity. Education: Ph.D. in Computer Science (University of Massachusetts Boston, 2023), MS in Mathematics (New York University, 2014), BA in Mathematics and Economics (Skidmore College, 2012) Her research explores cloud computing and networking with emphasis on machine learning and cybersecurity . Recent work addresses challenges in disaggregated storage systems , edge computing , and augmented reality . She received the DOE NNSA Joule Award (2022) for her scholarship. Her publications span topics including network congestion control , distributed file systems , and audio noise filtering . She teaches courses in cloud computing and computer networking .

• Photonic Interconnects
• Distributed Machine Learning
• Cloud Computing
• +۴ مورد دیگر

Rachee Singh is an Assistant Professor of Computer Science at Cornell University, leading the sysphotonics group which focuses on photonic interconnects and distributed machine learning systems. She is also an Amazon Scholar in the SageMaker Hyperpod team, specializing in large-scale ML infrastructure. Her research spans photonic fabrics for cloud workloads, WAN optimization, and secure networking. Key research interests include photonic interconnects for multi-accelerator servers, automated reasoning in network systems, and sustainability in cloud infrastructure. She has pioneered solutions like Aqua for memory offloading in LLMs and PipSwitch for programmable photonics-based circuit switching. Major grants include a 2024 NSF grant ($1M) for chip-to-chip photonic fabrics and DARPA/SRC funding via the JUMP 2.0 program. Notable awards include the 2025 Cisco Research Award and 2024 Amazon Research Award. Her work has been featured in top venues like ASPLOS, SIGCOMM, and NSDI. Rachee advises students such as Abhishek Vijaya Kumar (distributed ML) and Zhiying Xu (WAN optimization). Her sysphotonics group collaborates with industry partners like Amazon and Cisco, addressing challenges in photonic connectivity and planet-scale cloud systems.

Bruno DEFUDEمشاهده پروفایل

استاد

• Cloud Computing
• Data Integration
• Process Mining
• +۴ مورد دیگر

Prof. Bruno Defude is a Professor at Telecom SudParis, part of the University of Paris-Saclay. He has been affiliated with the institution since 1992, holding roles such as lecturer-researcher, department director, and currently serves as Deputy Director of Research and Doctoral Training. He leads the ACMES studies initiative and focuses on interdisciplinary research in distributed systems, cloud computing, and educational technologies. Education: Doctorate in Computer Science (1986), Grenoble INP Habilitation à Diriger des Recherches (HDR) (2005), UPMC Research Interests: Prof. Defude's work spans cloud computing architectures, data integration challenges, process mining, sensor networks, and adaptive learning systems. His contributions emphasize scalable solutions for distributed environments and privacy-aware service composition. Recent Trends: Recent publications highlight advancements in natural language querying of process data, multi-objective task scheduling in fog computing, and spatio-temporal data aggregation in vehicular networks. His work bridges theoretical foundations with practical implementations in distributed systems. Labs/Teams: Director of ACMES studies, involved in interdisciplinary research collaborations across computer science and telecommunications domains.

Chantal Taconetمشاهده پروفایل

مدرس

• Internet of Things (IoT)
• Middleware Systems
• Context-Aware Computing
• +۳ مورد دیگر

Chantal Taconet is a Lecturer at Telecom SudParis, part of the SAMOVAR research institute. Her work focuses on middleware systems for the Internet of Things (IoT), context-aware computing, energy efficiency, and blockchain applications in supply chains. She has co-authored over 20 peer-reviewed articles and conference papers since 2008, addressing IoT middleware design, QoC management, and middleware for cloud-IoT integration. Her research spans IoT middleware architectures (e.g., IoTVar framework), energy-efficient IoT protocols, and blockchain-based supply chain traceability. She contributed to the ANR INCOME project on multi-scale context management, emphasizing model-driven engineering and distributed system frameworks. Taconet has organized workshops like M4IoT and co-edited special issues on IoT middleware in Annals of Telecommunications . Key technical areas include semantic-based discovery services, fog computing integration for sensor networks, and trust models for IoT systems. Her work bridges theoretical middleware design with practical implementations for IoT applications.

Andreas Theocharisمشاهده پروفایل

استادیار

• Renewable Energy Systems
• Electrical Power Systems
• Smart Grids
• +۸ مورد دیگر

Andreas Theocharis is an Assistant Professor in Electrical Engineering at Karlstad University, specializing in Electrical Power Systems and Renewable Energy Systems Research. His research focuses on renewable energy integration, smart grid technologies, and advanced modelling of electrical components like transformers and photovoltaic systems. He collaborates with institutions such as Ellevio, KTH, Delft University of Technology, and industry partners like Siemens and Vestas. Teaching responsibilities include courses on electric circuits, power systems operation, renewable energy applications, and grid integration. His work bridges academia and industry, addressing challenges in sustainable energy systems through advancements in AI, machine learning, and IoT. Research contributions span photovoltaic generator modelling, battery storage optimization, and electromagnetic compatibility. Key publications address generative AI for renewable energy communities, uncertainty quantification in solar forecasting, and robust energy management strategies. Collaborations involve global networks with universities in the Netherlands, Norway, Greece, and industry leaders in energy sectors. His expertise in transformer dynamics and smart grid solutions supports practical implementations of sustainable energy frameworks.

Gianluca Aloiمشاهده پروفایل

دانشیار

• Wireless Networks
• Cellular Networks
• Sensor Networks
• +۷ مورد دیگر

Gianluca Aloi serves as an Associate Professor in Telecommunications (IINF-03/A) at the Department of Computer Engineering, Modeling, Electronics and Systems (DIMES) of the University of Calabria, Italy. He holds the position of scientific director for the Telecommunications and Information Theory for Advanced Networking Laboratory (TITAN Lab.). Dr. Aloi earned his PhD in Systems Engineering and Computer Science from the University of Calabria in 2003 and became a University Researcher in Telecommunications (ING-INF/03) in 2004 before advancing to his current academic rank. His research expertise spans wireless networks, cellular networks, sensor networks, Internet of Things systems and their interoperability, management of resources and services in the Cloud/Edge and IoT (CEI) Continuum, and management and orchestration of network resources using Artificial Intelligence. His work particularly focuses on UAV-assisted IoT systems for industrial applications, geological hazard monitoring, and maritime environments. Analysis of Dr. Aloi's recent publications (2023-2025) reveals a strong emphasis on applying reinforcement learning and deep learning techniques to solve complex networking challenges. His research shows a clear trajectory toward developing intelligent network architectures that optimize data collection, improve system resilience, and enhance resource management across the edge-to-cloud continuum. Key application areas include smart factories, disaster monitoring, and urban vehicular systems. Dr. Aloi teaches courses including Fundamentals of Telecommunications Networks and Telecommunications Networks for both Electronic Engineering and Computer Engineering programs. He maintains regular reception hours every Tuesday from 9am to 11am or by appointment via email. As scientific director of TITAN Lab, Dr. Aloi leads research initiatives focused on advanced networking technologies, with particular emphasis on developing solutions for next-generation communication systems that integrate artificial intelligence with traditional networking paradigms to address real-world challenges in telecommunications and IoT applications.

• Real-Time Systems
• Parallel Computing
• Cyber-Physical Systems
• +۳ مورد دیگر

Jing Li is an Assistant Professor at the Department of Computer Science in the Ying Wu College of Computing at New Jersey Institute of Technology. She holds a Ph.D. in Computer Science from Washington University in St. Louis (2017), advised by Chenyang Lu and Kunal Agrawal. Ph.D. in Computer Science, Washington University in St. Louis (2017) M.S. in Computer Science, Washington University in St. Louis (2014) B.S. in Computer Science, Harbin Institute of Technology, China (2011) Her research spans Real-Time Systems , Parallel Computing , Reinforcement Learning for System Design , and Scheduling Theory . Current projects include NSF-funded work on real-time systems with parallel resources and ARPA-E/IBM collaborations on reinforcement learning for converter design. Recent publications focus on AI-driven scheduling , parallel task optimization , and reinforcement learning applications in traffic control and circuit design. Key venues include AAAI, RTSS, PPoPP, and RTAS. Outstanding Achievement in Research (2022) Outstanding Paper Awards at RTSS (2018), RTAS (2016), ECRTS (2013) Turner Dissertation Award (2017) She advises graduate students in real-time systems and parallel computing, mentors NSF/ARPA-E projects, and leads professional services as TPC member and workshop organizer.

Eric Bartley Julمشاهده پروفایل

استاد

• Programming
• Object Oriented Programming
• Distributed Computing
• +۴ مورد دیگر

Eric Bartley Jul is a Professor in the Department of Informatics at the University of Oslo, specializing in Programming Technology within the Faculty of Mathematics and Natural Sciences. His research spans multiple domains of computer science with a focus on practical applications in medical imaging, distributed systems, and mobile computing. Professor Jul's research interests encompass a broad spectrum of computer science disciplines. His expertise lies particularly in Object-Oriented Programming, Distributed Computing, and Design Patterns, with expanding work in Cloud Computing and Security. His recent publications demonstrate a significant shift toward applying computer vision and deep learning techniques to medical diagnostics and healthcare applications, particularly in microcirculation analysis and reproductive medicine. This interdisciplinary approach bridges traditional computer science with cutting-edge medical research. His recent publication record shows a strong trend toward medical applications of computer vision and mobile sensor technologies. The 2024 papers reveal sophisticated applications of AI in reproductive medicine (sperm detection) and transportation monitoring (flight detection), while the 2022 publications establish his foundational work in medical imaging systems like CapillaryNet for blood flow analysis. This trajectory demonstrates a consistent focus on applying programming technology to solve complex real-world problems, particularly at the intersection of computing and healthcare. Professor Jul leads research within the Programming Technology group at the University of Oslo and is involved in several significant projects including A Modern Approach to Teaching Classes at the University Level in Theoretical Computer Science , Leveraging Energy-Aware Programming (LEAP) , and Reliable models of computation for concurrent and distributed problems . His work demonstrates strong collaborative efforts with researchers across multiple institutions, particularly with Paulo Ferreira and other colleagues at the University of Oslo.