Professor Dimitra Simeondiou
Professor of High Performance Networks and Director of the Smart Internet Lab | University of Bristol
Bristol, UNITED KINGDOM
Leading on mobile communications, 5G networks and the internet
Areas of Expertise (14)
Logistics
Digital Transformation in Vertical sectors including smart cities
optical communication
IT Networks
Telecommunications
Networks
WiFi
5G
Internet
Mobile Technology
Smart Cities
IT Infrastructures
5G/6G
Manufacturing
Biography
Dimitra Simeonidou is a Full Professor at the University of Bristol, the Co-Director of the Bristol Digital Futures Institute and the Director of Smart Internet Lab, leading on optical networks, network convergence, 5G/6G networks, and Internet infrastructure. Her research is focusing in the fields of high performance networks, programmable networks, wireless-optical convergence, 5G/B5G and smart city infrastructures. She is increasingly working with Social Sciences on topics of digital transformation for society and businesses. Professor Simeonidou has been the Technical Architect and the CTO of the smart city project Bristol Is Open. She is currently leading the Bristol City/Region 5G urban pilots.
She is the author and co-author of over 600 publications, numerous patents and several major contributions to standards. She has been co-founder of two spin-out companies, the latest being the University of Bristol VC funded spin-out Zeetta Networks, delivering SDN solutions for enterprise and emergency networks. Professor Simeonidou is a Fellow of the Royal Academy of Engineering, a Fellow of the IEEE and a Royal Society Wolfson Scholar.
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Education (3)
University of Essex: Ph.D., Optical Communications 1994
Aristotle University of Thessaloniki: M.Sc., Telecommunications 1989
Aristotle University of Thessaloniki: B.Sc., Physics 1987
Links (3)
Media Appearances (5)
Too late for UK Huawei rival but other domestic 5G options remain, experts say
Verdict online
2020-06-24
“I’m not sure if catching up with 5G is possible, but there are other opportunities there beyond traditional vendors,” said Dimitra Simeonidou, professor of high performance networks at the University of Bristol, speaking at the first evidence session of the Science and Technology Committee’s inquiry into the UK’s telecommunications infrastructure.
Dimitra Simeonidou, Smart Internet Lab: Building smarter cities
IoT News online
2020-03-11
“Last time we spoke, it was just the beginning of doing city–regional experimentation,” says Simeonidou. “We evolved our story from a Bristol city testbed to a regional testbed.“ “We installed 5G infrastructure at the centre of Bristol, 5G infrastructure at the centre of Bath – connected the two cities with fibre – and extended into our industrial park at Filton where our aerospace industry is sitting.”
Dimitra Simeonidou, Smart Internet Lab: Creating societal change with 5G
Telecoms Tech News online
2020-02-28
“We are looking at issues of end-to-end networking, service creation, and delivery,” explains Simeonidou. “For hardware and software core design, we have also worked quite intensively with vertical sectors like smart cities, transport, vehicles economy, and public safety.”
Professor Dimitra Simeonidou elected as Fellows of the Royal Academy of Engineering
TechSpark online
2019-10-02
Professors Dimitra Simeonidou from the University of Bristol’s Faculty of Engineering has been elected as a Fellow of the Royal Academy of Engineering in recognition of her outstanding and continuing contributions to the profession.
Hologram phone calls - sci-fi or serious possibility?
BBC News online
2018-09-20
Experts do see barriers to the rise of 5G apps for consumers, though. According to Dimitra Simeonidou, a professor in high performance networks at Bristol University, many people may not be able to afford the first 5G-ready handsets or accompanying equipment like VR glasses.
Articles (5)
Auto-3P: An autonomous VNF performance prediction & placement framework based on machine learning
Computer Networks
2020 We propose Auto-3P, an Autonomous module for Virtual Network Functions Performance Prediction and Placement at network cloud and edge facilities based on Machine Learning (ML). Auto-3P augments the autonomous placement capabilities of MANagement and Orchestration frameworks (MANOs) by considering both resource availability at hosting nodes and the implied impact of a VNF node placement decisions on the whole service level end-to-end performance.
IEEE TCCN Special Section Editorial: Intelligent Resource Management for 5G and Beyond
IEEE Transactions on Cognitive Communications and Networking
2020 Learning from massive network data to produce cognitive knowledge for efficient resource management in 5G and beyond 5G (B5G) is still challenging. We are delighted to introduce the readers to this special section of the IEEE Transactions on Cognitive Communications and Networking (TCCN), which aims at exploring recent advances and addressing practical challenges in the intelligent resource management in 5G/B5G.
11.2 Tb/s Classical Channel Coexistence with DV-QKD over a 7-Core Multicore Fiber
IEEE Explore
2020 The feasibility of transmitting discrete-variable quantum key distribution channels with carrier-grade classical optical channels over multicore fibers is experimentally explored in terms of achievable quantum bit error rates, secret key rates as well as classical signal bit error rates.
5GUK Exchange: Towards sustainable end-to-end multi-domain orchestration of softwarized 5G networks
Computer Networks
2020 5G networks envisage to support a range of vertical industries, circumventing any potential barriers from converging various network technologies and administrative domains. Current solutions focus only on provisioning services within single administrative domains. There is also lack of standards for sustainable end-to-end multi-domain solutions that can use existing Network Function Virtualization (NFV) Management and Orchestration (MANO) systems.
End-to-End Performance-based Autonomous VNF Placement with adopted Reinforcement Learning
IEEE Transactions on Cognitive Communications and Networking
2020 The autonomous placement of Virtual Network Functions (VNFs) is a key aspect of Zero-touch network and Service Management (ZSM) in Fifth Generation (5G) networking. Therefore, current orchestration frameworks need to be enhanced, accordingly. To address this need, this work presents an Adapted REinforcement Learning VNF Performance Prediction module for Autonomous VNF Placement, namely AREL3P.
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