جست‌وجوی استاد و پژوهشگر

• Cloud Computing
• Machine Learning
• Computer Networks
• +۳ مورد دیگر

Hamed Hamzeh serves as Lecturer in Data Science at the School of Computer Science and Engineering, University of Westminster, and is affiliated with the Centre for Parallel Computing. His academic credentials include a Ph.D. in Cloud Computing from Bournemouth University and an MSc in Data Science from Istanbul Sehir University, Turkey. Dr. Hamzeh's research centers on cloud-native resource management, computer networks, and multi-agent systems, with groundbreaking work on fairness in cloud resource allocation. He developed novel algorithms including H-FFMRA and MRFS that address multi-resource scheduling in heterogeneous environments. His expertise spans AWS, Kubernetes, Python, and optimization techniques, bridging theoretical cloud computing with industrial applications in orchestration and resource management. Analysis of his 11 publications (2017-2023) reveals an evolving research trajectory: beginning with network bandwidth allocation (2017), advancing to cloud resource fairness (2018-2021), and culminating in cloud-to-things continuum orchestration (2023). This progression demonstrates increasing system complexity while maintaining core focus on fairness metrics across distributed environments. Dr. Hamzeh actively contributes to the academic community as technical committee member for IEEE ICCCS and Distributed AI conferences, and as reviewer for Springer's Journal of Grid Computing and Journal of Supercomputing. His service reflects recognition within cloud computing research circles. Prospective students receive supervision in Cloud Computing, Artificial Intelligence, Machine Learning, Software Engineering, and Computer Networks. Current research opportunities emphasize practical implementation of resource allocation algorithms in cloud-native environments through the Centre for Parallel Computing.

Filipe Barrocas Limaمشاهده پروفایل

دانشیار

• Communication
• Multimedia Communication
• Health Communication
• +۳ مورد دیگر

Filipe Barrocas Lima serves as an Associate Professor at the Lisbon School of Social Communication (ESCS-IPL) within the Polytechnic Institute of Lisbon and maintains a secondary affiliation with the Leiria School of Education and Social Sciences (ESECS-IPL) at the Polytechnic Institute of Leiria. His instructional focus includes multimedia communication, content production, and communication design within the Department of Audiovisual and Multimedia. Educational background: Bachelor's degree in Audiovisual and Multimedia from ESCS-IPL Specialist Degree in Audiovisual and Multimedia Communication from Polytechnic of Lisbon (IPL) PhD candidate in Communication Sciences at NOVA FCSH (Faculty of Social Sciences and Humanities, Universidade Nova de Lisboa) His research examines mental health literacy in streaming content, bridging academic theory with over a decade of professional communications consulting experience. Primary research domains include Communication, Multimedia Communication, Health Communication, Mental Health Literacy, and Streaming Media, with significant contributions to health and wellness communication applications. Professional narrative: Combines academic instruction with extensive industry experience in health communication consulting, focusing on practical applications of streaming media for mental health awareness. Current doctoral research at NOVA FCSH represents his primary scholarly contribution, investigating how streaming platforms influence mental health literacy.

• Video Quality Assessment
• Telecommunications
• Quality of Service (QoS)
• +۵ مورد دیگر

Professor Tadeus Uhl is a faculty member at the University of Applied Sciences Flensburg in the School of Information and Communication. His research focuses on telecommunications, video quality assessment, and Quality of Service (QoS) technologies. He maintains an active research profile with numerous publications spanning from 2017 to 2024. Professor Uhl's research interests center around video quality evaluation, telecommunications technologies, and network performance analysis. His work examines cutting-edge topics including 8-bit and 10-bit MP4 coding, machine learning applications for video quality assessment, and user experience with different video resolutions (1K, 2K, and 4K). He has also conducted significant research on 5G technology, VoIP systems, and Quality of Service in IoT environments. His recent publications show a clear trend toward video quality assessment using modern machine learning techniques, with a focus on real-world streaming services like Netflix. His work bridges theoretical network performance concepts with practical applications in video streaming, cellular networks, and offshore communication systems. Professor Uhl has made substantial contributions to understanding Quality of Service parameters across various communication technologies, from traditional VoIP systems to modern IoT networks and offshore wind farm communications infrastructure. His research has been published in notable venues including IEEE conferences, the Journal of Telecommunications and Information Technology, and various scientific journals focused on telecommunications and multimedia technology.