جستجوی استاد راهنمای دانشگاهی

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 .

• Industry 4.0
• Cyber-Physical Systems
• Industrial Automation
• +۷ مورد دیگر

Veera Ragavan Sampath Kumar is a Senior Lecturer at the Malaysia School of Engineering, Monash University. With over 17 years of industrial experience in factory automation and systems integration, his research focuses on Industry 4.0, Cyber-Physical Systems, Robotics, and Machine Learning. He holds leadership roles in IEEE technical committees, including Co-Chair of the IEEE Working Group for Ontologies in Autonomous Robotics (IEEE1872.2 AuR). Research Interests: Industry 4.0, Cyber-Physical Systems, Real-time Embedded Systems, Robotics, Industrial IoT, Machine Learning Projects: Agriculture 4.0 (2023-2025), Model Synthesis Framework for CPS (2015-2018) Collaborations: IEEE Robotics and Automation Society, ASME, IEEE Standards Association His work aligns with UN SDGs, particularly in advancing sustainable manufacturing and technology. Teaching commitments include TRC2001 (Systems Engineering) and TRC3000 (Mechatronics Project II).

• Software Engineering
• Cybersecurity
• Cloud Computing
• +۳ مورد دیگر

Georg Simhandl is affiliated with the Faculty of Computer Science, specifically within the Research Group Software Architecture. His work focuses on advancing theoretical and practical aspects of software engineering with a strong emphasis on cybersecurity, microservices, and empirical studies. Research Interests: His core research spans Microservices Architecture , Cybersecurity in Software Systems , Formal Methods , and Empirical Software Engineering . He investigates topics such as secure firmware updates, threat modeling for microservices, and developer cognition in system maintenance. Recent work highlights include leveraging TPMs for cryptographic anchoring and analyzing how dataflow diagrams enhance security analysis. Activities: He has presented at conferences like the ACM SIGPLAN International Conference on Software Language Engineering (SLE '24) and participated in workshops such as the IEEE/ACM International Workshop on Eye Movements in Programming (EMIP). His research bridges theoretical frameworks with practical software development challenges. Labs/Teams: Works within the Research Group Software Architecture, contributing to projects on secure architecture design and empirical evaluation of software practices.

• 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.

• Decentralized Machine Learning
• Federated Learning
• Industry 4.0
• +۳ مورد دیگر

Alessio Mora is a postdoctoral researcher at the Department of Computer Science and Engineering (DISI), University of Bologna, specializing in decentralized learning techniques such as Federated Learning. His work focuses on communication efficiency, heterogeneous data handling, and distributed AI systems. PhD in Computer Science and Engineering, University of Bologna (2023) Master in Computer Engineering, University of Bologna (2019) Bachelor in Computer Engineering, University of Bologna (2016) His research spans decentralized learning, federated learning, and their applications in Industry 4.0, IoT, and edge computing. Key themes include model optimization, communication efficiency, and heterogeneous data distribution in cross-device settings. Recent publications highlight trends in federated learning infrastructure, including unlearning methods, knowledge distillation, and sparse compression techniques. His work integrates theoretical analysis with practical implementations in industrial and IoT contexts. Summer of Reproducibility Award – Flower Labs (2023) Awarded $2,000 USD for implementing and reproducing the FedMLB baseline in Flower, advancing reproducibility in federated learning. Mora has contributed to European projects like OntoTrans and SimDOME, focusing on ontology-based systems for materials modeling and industrial data translation. His technical expertise includes Docker, Stardog triplestore, FastAPI, and Python wrappers for chemical simulation tools.

• Cloud Computing
• Edge Computing
• Middleware
• +۷ مورد دیگر

Lorenzo Rosa is a PhD student in Computer Science and Engineering at the University of Bologna, affiliated with the Interdepartmental Center for Industrial Research on ICT and part of the Mobile Middleware Research Group under Prof. Antonio Corradi. He collaborates with Prof. Ken Birman's group at Cornell University on the Cascade project , focusing on cloud and edge computing for high-availability industrial applications. Education : PhD candidate (ongoing) in Computer Science and Engineering, University of Bologna Master's in Computer Engineering (110/110 cum laude), University of Bologna Visiting scholar at Cornell University during thesis preparation Research Focus : Integrating kernel-bypassing communication technologies (RDMA, DPDK, XDP, TSN) into virtualized and distributed industrial applications across cloud continuum infrastructures. Developing middleware solutions with homogeneous interfaces for heterogeneous technologies. Labs & Collaborations : Member of Mobile Middleware Research Group (University of Bologna) External collaborator for Cascade project (Cornell University, since 2020) Collegio Superiore alumnus (University of Bologna)

• Distributed Systems
• Computer Networks
• Peer-to-peer Algorithms
• +۶ مورد دیگر

Öznur Özkasap is a Professor in the Department of Computer Engineering at Koc University's Graduate School of Sciences and Engineering. She serves as Head of Department and has research interests spanning distributed systems, computer networks, and energy-efficient networking protocols. Her work integrates artificial intelligence into distributed computing frameworks and explores security in peer-to-peer systems. Education: PhD (2000), MSc (1994), and BS (1992) from Ege University Research Areas: Distributed Systems, Cloud/Edge Computing, Network Security, and AI applications in distributed environments Her recent publications focus on blockchain-assisted distributed systems, federated learning optimization, and energy-efficient frameworks for software-defined networks. She explores multi-objective load balancing, decentralized energy trading, and secure P2P architectures. Key trends include cross-disciplinary applications of distributed computing in healthcare and energy systems. Professor Özkasap contributes to advancing edge computing, IoT-based sensor systems, and privacy-preserving mechanisms in decentralized environments. Her work addresses challenges in reliable network protocols, microgrid energy sharing, and security vulnerabilities in autonomous systems.