جست‌وجوی استاد و پژوهشگر

• Social Network Analysis
• Misinformation Detection
• Human Mobility Modeling
• +۴ مورد دیگر

Jussara M. Almeida is an established computer science researcher specializing in social network analysis, misinformation detection, and human mobility modeling. Her extensive publication record (1996–2025) demonstrates active research in web science, political communication on messaging platforms (WhatsApp/Telegram), and cloud systems. She frequently collaborates with Brazilian institutions and international partners on large-scale data projects. Research Focus: Her core interests include: Modeling information diffusion in encrypted messaging apps (WhatsApp/Telegram) Predicting human mobility patterns and privacy implications Analyzing political discourse and election-related coordination online Developing computational methods for misinformation detection Optimizing cloud/edge computing performance Publication Trends: Recent work (2021-2025) shows intensified focus on: Telegram's role in political mobilization and information dissemination Advanced techniques for identifying fake news websites and image-based misinformation Privacy-preserving mobility analysis and edge computing Child safety in live-streaming platforms Collaborations & Impact: Key collaborators include Marcos André Gonçalves, Fabrício Benevenuto, and Marco Mellia. Her research provides critical insights into real-world problems like election integrity, platform governance, and user privacy.

Leonardo Banhمشاهده پروفایل

پژوهشگر

• Generative AI
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Leonardo Banh is a Researcher at the University of Duisburg-Essen within the Faculty of Computer Science and its Chair of Business Information Systems and Software Engineering . M.Sc. in Business Information Systems (University of Duisburg-Essen, 2022) B.Sc. in Business Information Systems (University of Duisburg-Essen, 2020) Semester abroad at Instituto Superior Técnico, Lisbon (2021) His research focuses on Generative AI and its socio-technical implications, particularly in Machine Learning and Deep Learning applications. He explores intersections with NeuroIS , Smart Tourism , and E-commerce Ecosystems , emphasizing sustainability and digital transformation. Recent publications analyze Generative AI in Software Engineering , AI in Music Sentiment Analysis , and AI-Based Sign Language Translation . His work often involves design science research and grounded theory frameworks. Best Paper in Track Award (ICIS 2024) Nominated for Best Paper Award (ICIS 2024) Outstanding Reviewer (ICIS 2024) As advisor, he supervises theses on topics including AI-Based Mental Health Chatbots , Generative AI in HR , and Smart Tourism Applications . He also contributes to the Institute of Computer Science and Information Systems and serves on appointment/habilitation committees.

• Wireless Communication
• Edge Computing
• Network Security
• +۳ مورد دیگر

Yao Zhu is a Visiting Professor at the Chair of Information Theory and Data Analytics, RWTH Aachen University . His research focuses on advanced wireless communication systems, particularly in Edge Computing , Ultra-Reliable Low-Latency Communication (URLLC) , and Physical Layer Security , leveraging Finite Blocklength Codes for next-generation network optimization. Key research areas include: Optimization of resource allocation and task scheduling in distributed edge learning and fog computing environments Reliability and energy efficiency trade-offs in Industrial IoT and V2X networks Novel applications of NOMA (Non-Orthogonal Multiple Access) and short-packet communication for secure and fresh data transmission Integration of physical layer deception with semantic reliability models His work explores the interplay between telecommunications and computer science principles to address challenges in low-latency, high-reliability networked systems. The Chair of Information Theory and Data Analytics serves as his academic base, focusing on theoretical and practical advancements in data-driven communication frameworks.

• Wireless Communications
• Internet of Things (IoT)
• Edge Computing
• +۷ مورد دیگر

Zheng Chang is a Professor at the Institute of Computing Technology, School of Computer Science and Technology, University of Chinese Academy of Sciences in Beijing, China. With a PhD from the University of Jyväskylä (2013), Chang has established a prolific research career with over 240 publications spanning from 2011 to 2025. Chang maintains strong collaborative ties with researchers at the Chinese Academy of Sciences' Shenyang Institute of Automation and has developed significant international collaborations, particularly with Finnish researchers including Timo Hämäläinen. Chang's research focuses on cutting-edge areas at the intersection of wireless communications, artificial intelligence, and edge computing. Their work prominently features federated learning, UAV networks, resource allocation, and privacy-preserving techniques for IoT applications. Recent publications demonstrate a strong emphasis on vehicular edge intelligence, split learning architectures, and RIS-assisted communications. The research output shows consistent growth with 42 publications in 2024 alone, indicating an active and expanding research program. Chang's 15 most recent publications reveal a clear research trajectory toward addressing the challenges of resource-constrained edge environments through innovative learning architectures. The work spans theoretical frameworks for privacy preservation in federated learning to practical implementations for UAV networks and vehicular systems. A notable trend is the integration of AI-generated content techniques with traditional federated learning approaches to overcome data scarcity issues in edge environments. While specific awards aren't documented in the provided text, Chang's extensive publication record in top-tier IEEE journals including IEEE Transactions on Wireless Communications, IEEE Internet of Things Journal, and IEEE Transactions on Vehicular Technology demonstrates significant scholarly impact. The research has been widely cited, with multiple highly cited co-authors including Timo Hämäläinen (66 co-authored papers), Zhu Han (38 papers), and Geyong Min (31 papers). Chang's work shows strong practical applications across multiple domains including intelligent transportation systems, smart agriculture, healthcare IoT, and next-generation 6G networks. The research program appears well-funded through collaborations with major institutions and demonstrates clear translational potential for real-world deployment in edge computing environments.

• Wireless Communications
• Signal Processing
• MIMO Systems
• +۶ مورد دیگر

Claude D'Amours is a Professor in the Department of Electrical and Computer Engineering at the University of Ottawa, Faculty of Engineering. With a research career spanning over two decades, his work has significantly contributed to the fields of wireless communications, signal processing, and network security. His current research focuses on cutting-edge technologies including 5G/6G networks, UAV communications, reconfigurable intelligent surfaces, and physical layer security. Dr. D'Amours' research interests center on advanced wireless communication systems, with particular emphasis on MIMO technologies, CDMA systems, spectrum sensing techniques, and channel modeling for emerging applications. His work bridges theoretical foundations with practical implementations, addressing critical challenges in modern wireless networks including interference management, security vulnerabilities, and efficient resource allocation. Recent research has expanded into UAV communications, where he investigates channel characteristics and reliability issues in drone-based networks. Analysis of his recent publications reveals a strong focus on security aspects of wireless communications, particularly physical layer security mechanisms to counter jamming attacks and eavesdropping. His work on RF fingerprinting for device authentication in industrial IoT settings demonstrates practical applications of his theoretical research. The trend in his publications shows increasing attention to 5G/6G technologies, with particular emphasis on millimeter wave communications, hybrid precoding architectures, and novel approaches to spectrum sharing. Multiple publications on UAV-to-ground channel modeling and performance analysis Research on physical layer security mechanisms against jamming attacks Work on hybrid precoding architectures for mmWave MIMO systems Studies on RF fingerprinting for secure industrial IoT applications Investigations into spectrum sensing techniques for cognitive radio Dr. D'Amours maintains active research collaborations with numerous colleagues, particularly Michel Kulhandjian, Hovannes Kulhandjian, and François Chan, resulting in a consistent stream of high-impact publications across top-tier IEEE journals and conferences. His research group appears to focus on both theoretical analysis and practical implementation of advanced wireless communication techniques, with applications spanning from critical mission communications to industrial IoT security.

Hai Dongمشاهده پروفایل

مدرس ارشد

• Service-Oriented Computing
• Edge Intelligence
• Blockchain
• +۴ مورد دیگر

Dr. Hai Dong is a Senior Lecturer at the School of Computing Technologies, RMIT University in Melbourne, Australia, with promotion to Associate Professor scheduled for 2026. He serves as the Founding Director of the CloudTech-RMIT Green Cryptocurrency Joint Research Laboratory (GreenCryptoLab) and Leader of the Smart Sensing and Services Research Area. Previously, he held research fellow positions at both RMIT University and Curtin University. Dr. Dong is a Senior Member of IEEE and chairs the IEEE Computational Intelligence Society Task Force on Deep Edge Intelligence. Dr. Dong's research spans several cutting-edge domains including Service-Oriented Computing, Edge Intelligence, Blockchain, AI Security, Cyber Security, and Machine Learning. His work bridges theoretical foundations with practical applications, particularly in secure and efficient computing systems. He has developed innovative approaches for smart contract security, edge computing optimization, federated learning, and blockchain applications with a strong focus on sustainability and real-world impact. His publication record demonstrates consistent high-impact contributions across top venues including AAAI, ASE, ICML, TSE, and TSC. Dr. Dong's research shows a clear trajectory toward increasingly sophisticated integration of AI with edge computing and blockchain systems, with growing emphasis on security, privacy, and resource efficiency. Recent work highlights his leadership in addressing emerging challenges in LLM-generated smart contracts and secure federated learning systems. Best Research Paper Award at ICSOC 2016 Best Paper Award at IEEE ICBC 2025 2023 RMIT Award for Research Engagement and Impact - Industry Engagement in Graduate Research Dr. Dong has successfully supervised numerous PhD and Master's students to completion, with many going on to prestigious positions. He has secured over $5 million in research funding as Chief Investigator from sources including ARC, CRC, QNRF, and industry partners like ANZ, CloudTech, and Telstra. His GreenCryptoLab research facility represents a significant industry-academic partnership focused on sustainable blockchain technologies. Dr. Dong maintains active collaborations with researchers worldwide and serves on committees for over 100 international conferences.

Stefan Lankesمشاهده پروفایل

پژوهشگر

• Operating Systems
• System Software
• High-Performance Computing
• +۴ مورد دیگر

Dr. rer. nat. Stefan Lankes is an academic researcher at the Chair of Automation of Complex Power Systems, RWTH Aachen University's Faculty of Electrical Engineering and Information Technology. His work focuses on operating systems, high-performance computing (HPC), cloud computing, and lightweight virtualization techniques for embedded and real-time systems. Stefan holds a PhD in Electrical Engineering (2003) for his dissertation on real-time distributed platforms. His career spans roles from Scientific Assistant (1998-2004) to Academic Director (since 2019), with key contributions to HPC infrastructure and simulation environments. Research highlights include Rust-based OS development ( HermitCore unikernel ), GPU virtualization in distributed systems, and energy-efficient embedded computing paradigms. He pioneered the FlippedOS digital teaching platform using virtual workstations for operating systems education. Scientific awards include the 2016 Digital Teaching Fellowship and the 2021 RWTH Lecturer distinction. His publications cover topics from NUMA memory management to real-time CORBA protocols, with recent works addressing unikernel security and CUDA virtualization. Stefan leads simulation infrastructure and HPC virtualization projects, with affiliations to the E.ON Energy Research Center and involvement in European workshops like Euro-Par. His work bridges system software innovation with practical applications in energy systems and supercomputing.

• Distributed Systems
• Service-Oriented Computing
• Cloud Computing
• +۴ مورد دیگر

Winfried Lamersdorf is a full professor in the Department of Computer Science at the University of Hamburg , leading the Distributed Systems (VSIS) research unit. His career spans from IBM's European Networking Centre to leading numerous DFG, EU, and industry-funded projects. Major research interests include: Service-oriented computing (SOA, Web Services) Mobile and ubiquitous systems Agent-oriented software construction Self-organizing systems Context-aware middleware Cloud/edge computing Applications in E-Health, Smart Cities, and Industrial Informatics Recent projects like SANE (Smart Networks for Citizen Participation), CloudAware (context-adaptive mobile cloud systems), and FYPA²C (future production automation) highlight his focus on urban data spaces, energy-efficient mobile systems, and evolutionary software management. His scientific contributions span 200+ publications, with 15 recent articles covering topics such as: Complex event processing Decentralized blockchain coordination Context-aware computation offloading Model-driven production system evolution BDI agent architectures Service composition patterns Advising over 20 PhD students including Heiko Bornholdt (Smart Cities), Philipp Kisters (Distributed Platforms), and Gabriel Orsini (Mobile Clouds, 2016), Lamersdorf has shaped research in distributed applications through long-term collaborations with institutions like TU Munich, HSU Hamburg, and international IFIP committees.

Anton Semjonovمشاهده پروفایل

پژوهشگر

• Computation Offloading
• Edge Computing
• Distributed Systems
• +۷ مورد دیگر

Anton Semjonov is a Research Associate in the Distributed Operating Systems (DOS) group at the Department of Informatics, University of Hamburg, working under Prof. Dr. Janick Edinger. He also leads the interdisciplinary Creative Lab "base.camp" at the faculty level, fostering student innovation and real-world problem solving. His academic journey includes a Master’s in Informatics with a focus on Information Security from Universität Hamburg (2023) and a Bachelor’s in General Engineering Science with a focus on Computer Science from TU Hamburg (2020). Master of Science, Informatics (Information Security), Universität Hamburg, 2023 Bilingual Bachelor of Engineering, General Engineering Science (Computer Science), TU Hamburg, 2020 His research focuses on computation offloading and edge computing, particularly through browser-based middleware like Wasimoff, which leverages WebAssembly to enable zero-setup, volunteer-driven distributed computing. He also investigates coordination in distributed systems and information security, with publications at Middleware and IEEE PerCom. His work extends into computer science education, where he analyzes how creative labs bridge gaps in traditional curricula. The most recent articles highlight a strong trend in decentralized, secure, and scalable computing frameworks that utilize idle edge devices through web browsers. These works emphasize real-world deployment, performance evaluation, and the integration of privacy-preserving and context-aware mechanisms in heterogeneous environments. There is a clear interdisciplinary thread combining systems research with educational innovation. No scientific awards have been mentioned in the provided materials. Anton Semjonov is actively involved in research advising through his leadership in the DOS group and the base.camp lab. He contributes to research projects such as DDLitLab's LegalGPT initiative. While no formal grants are listed, his ongoing contract and project involvement suggest active funding support. He collaborates with Prof. Edinger and other researchers on distributed systems and AI applications. He is a key member of the Distributed Operating Systems research group and leads the Creative Lab "base.camp," which serves as an interdisciplinary platform for students to develop innovative solutions to real-world problems. These environments support open-ended, exploratory learning and promote collaboration across academic and societal domains.

• Edge Computing
• Internet of Things
• Vehicular Networks
• +۵ مورد دیگر

Muhammad Bilal is an Associate Professor at Zhejiang University's School of Computer Science, Department of Computer Science and Technology. His research spans multiple cutting-edge domains in computer science and engineering, with a particular focus on edge computing, Internet of Things, and vehicular networks. His research interests include Edge Computing , Internet of Things , Vehicular Networks , Federated Learning , Digital Twins , and Cloud Computing . His work addresses critical challenges in resource allocation, latency optimization, privacy preservation, and intelligent decision-making in distributed computing environments. He has made significant contributions to developing novel frameworks for service caching, computation offloading, and secure data processing in next-generation networks. His recent publications reveal a strong trend toward integrating artificial intelligence with edge and cloud infrastructure, particularly focusing on privacy-preserving techniques and resource-efficient algorithms. His work spans applications from intelligent transportation systems to healthcare monitoring and meteorological services, demonstrating the versatility and real-world impact of his research. Dr. Bilal has established a prolific publication record with numerous high-impact papers in top-tier journals and conferences, reflecting his active engagement in the academic community. His collaborative approach is evident through extensive co-authorship networks, particularly with researchers in China, Pakistan, and internationally.

• Blockchain Technology
• Edge Computing
• Federated Learning
• +۴ مورد دیگر

Pubudu N. Pathirana is a Professor at the University of Melbourne's College of Engineering, specializing in Blockchain Technology, Edge Computing, Federated Learning, and Machine Learning for Healthcare . His work bridges theoretical advancements with practical applications in smart cities, cyber-physical systems, and medical diagnostics. Education : PhD in Electrical Engineering, Monash University His research focuses on privacy-preserving machine learning and blockchain integration with edge networks , demonstrated through collaborations with Dinh C. Nguyen, Minh K. Quan, and Bipasha Kashyap. Key contributions include quantum-enhanced models for acoustic classification and federated learning frameworks for IoT environments. Recent publications (2025) highlight advancements in spatio-temporal traffic modeling , adaptive privacy clipping , and secure client aggregation . Earlier work (2021-2024) explored applications in Covid-19 detection , Friedreich Ataxia severity classification , and entropy-based cerebellar ataxia analysis . He mentors students like Ali Reza Sattarzadeh and Kanishka Ranaweera, with grants supporting projects on blockchain-enhanced federated learning and quantum-inspired edge computing . His lab collaborates with institutions such as Monash University and the Florey Institute of Neuroscience.

• Blockchain Technology
• Smart Grids and Energy Systems
• Artificial Intelligence
• +۵ مورد دیگر

Tudor Cioara is a Professor at the Department of Computer Science, Faculty of Mathematics and Computer Science, Babeș-Bolyai University in Romania. With over 100 publications spanning from 2008 to 2025, his research establishes him as a leading academic in the intersection of computer science and energy systems. His research interests focus on blockchain technology applications in energy systems, smart grid optimization, distributed computing, and AI-driven energy management. Cioara's work bridges theoretical computer science with practical energy applications, developing novel approaches for peer-to-peer energy trading, virtual power plants, and data center energy optimization. His recent work has expanded into federated learning, edge computing, and large language models applied to energy systems. Cioara's publication portfolio shows a consistent trajectory of increasing impact, with significant contributions in 2023-2025 focusing on AI-driven energy solutions, blockchain applications, and healthcare technology integration. His work demonstrates strong interdisciplinary connections between computer science, electrical engineering, and healthcare domains. He has received recognition through numerous collaborations with international researchers and institutions, particularly in European energy and computing projects. His work on blockchain-based energy trading systems and AI optimization for smart grids represents some of the most influential contributions in his field. Cioara leads a research group that has produced significant work on data center optimization, energy flexibility management, and digital twin applications for energy systems. His team has developed innovative approaches for integrating renewable energy sources, managing electric vehicle charging, and creating secure energy trading platforms using blockchain technology.

• 5G/6G Networks
• Wireless Networks
• Mobility Management
• +۵ مورد دیگر

M.Sc. Anna Prado is a Research and Teaching Associate at the Chair of Communication Networks (Prof. Kellerer) at the Technical University of Munich. She holds a B.Sc. in Information Systems and Communication Engineering from Bauman Moscow State Technical University (2017) and an M.Sc. in Communication Engineering from TUM (2020). She is currently pursuing her Ph.D., focusing on mobility management in 5G/6G networks, simulation of wireless systems, and digital twins for 6G. Her research emphasizes minimizing handover occurrences while ensuring smooth user connectivity through optimization and reinforcement learning techniques. Anna's academic role involves contributing to projects like the BMBF-funded 6G-ANNA initiative, which aims to develop holistic 6G systems prioritizing security, sustainability, and flexibility. She collaborates on network architecture design, resource allocation strategies, and resilient communication frameworks. Her work aligns with German technological sovereignty goals, addressing industrial and societal needs through advanced network technologies. Her research interests span 5G/6G networks, wireless resource management, digital twins, and machine learning applications in networks. She has authored/co-authored peer-reviewed papers on topics like admission control, slice dimensioning, energy-efficient edge orchestration, and secure 6G architectures. Her contributions enhance network efficiency, reliability, and adaptability for future communication systems. Anna is actively involved in the FlexComNetsLab and 6G-IP Lab, testing and demonstrating innovative 6G concepts. She participates in conferences and collaborates with industry partners to bridge academic research and real-world deployment.

• Parallel Computer architectures
• High Performance Computing
• Multi-/Manycore architectures
• +۵ مورد دیگر

PD Dr. Josef Weidendorfer is a qualified private lecturer at Technische Universität München (TUM) and leads the Future Computing Group at the Leibniz Computing Centre (LRZ). He holds a dual affiliation with TUM's Department of Informatics, Chair of Computer Architecture and Parallel Systems (Prof. Schulz), and the Leibniz Rechenzentrum der Bayerischen Akademie der Wissenschaften. His work focuses on developing smooth migration strategies for future HPC systems and evaluating novel technologies to improve system-level and workload analysis tools. Weidendorfer's research interests encompass Parallel Computer Architectures, High Performance Computing, Multi-/Manycore architectures, GPGPU, Performance analysis and optimization, Cache Simulation, Virtual Machines, and dynamic code generation. He is particularly interested in strategies for improving computational efficiency across various hardware structures, including specialized accelerator hardware for HPC codes. He regularly organizes the UCHPC workshop (since 2010 with Euro-Par) about unconventional hardware for HPC computing and is co-organizer of the PSTI workshop series. His recent publications reveal a strong focus on HPC system optimization, with particular emphasis on load balancing techniques, cache partitioning, application malleability, and performance monitoring. The research trajectory shows increasing attention to practical implementation challenges in modern heterogeneous computing environments, especially regarding GPU utilization, resource partitioning under power constraints, and phase-aware system monitoring. Weidendorfer maintains the open-source tools Callgrind/KCachegrind for cache simulation and has supervised numerous student projects across bachelor's, master's, and guided research programs. He teaches courses including Virtualization Techniques, Parallel Programming Systems, and Advanced Computer Architecture, demonstrating strong commitment to both research and education in computer architecture and parallel systems. As principal investigator for multiple large-scale projects including EU Project SEANERGYS (2025-2028) and BMBF Project ScalNext (2022-2025), he leads significant research initiatives focused on future computing technologies and HPC system development.

Vittorio Cozzolinoمشاهده پروفایل

پژوهشگر

• Edge Computing
• Computer Vision
• Lightweight Virtualization
• +۷ مورد دیگر

Vittorio Cozzolino is a PhD Researcher at the Technical University of Munich since 2015, supervised by Professor Jörg Ott. His work focuses on edge-cloud infrastructures , unikernels , and distributed orchestration frameworks . He previously worked at AgileLab (Turin, Italy) as a Technical Lead and completed an ERASMUS internship at IMDEA Networks (Madrid, Spain) studying MANETs. M.Sc. in Computer Science and Engineering, University Federico II of Naples (2014) His research interests include edge computing architectures , lightweight virtualization , and computer vision for mobile augmented reality . Publications highlight trends in edge-cloud collaboration , unikernel-based systems , and IoT security . He actively contributes to teaching courses on edge computing , recommender systems , and networking fundamentals .