Dimitra Simeonidou
telecommunications researcher
Facts
10 properties- Instance of
- human
- Occupation
- engineer
- Employer
- University of Bristol[3]
- Field of work
- telecommunications[2]
- Educated at
- University of Essex[4]
- Award received
- Fellow of the Royal Academy of Engineering[5]
- Academic thesis
- An experimental investigation of Raman and erbium doped fibre amplifiers for use in optical communication systems[7]
- Imported from
- wholeness_audit_2026-05-02
🏷️ Also known as
en Dimitra E. Simeonidou
en Dimitra Simeonidou
🔖 Identifiers · 9
- ORCID iD
- 0000-0002-7046-544X
- VIAF cluster ID
- 305647694
- OpenAlex ID
- A5030580652, A5057771065, A5126608584, A5135299981, A5136372959as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
- ACM Digital Library author ID
- 81321488071
- DBLP author ID
- 23/5432
- Google Knowledge Graph ID
- /g/11h7q4m3ty
- Google Scholar author ID
- qK5hDQgAAAAJ
- IEEE Xplore author ID
- 37264943100
- X (Twitter) username
- dsimeo (2012–present)
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 29
5G infrastructures supporting end-user and operational services: The 5G-XHaul architectural perspective,
ANN-Based Multi-Channel QoT-Prediction Over a 563.4-km Field-Trial Testbed,
A Novel Autonomous Profiling Method for the Next-Generation NFV Orchestrators,
Auto-3P: An autonomous VNF performance prediction & placement framework based on machine learning,
Coexistence of Quantum and 1.6 Tbit/s Classical Data Over Fibre-Wireless-Fibre Terminals,
Deep Reinforcement Learning-Based Policy for Baseband Function Placement and Routing of RAN in 5G and Beyond,
Deep-reinforcement-learning-based RMSCA for space division multiplexing networks with multi-core fibers [Invited Tutorial],
Deep Reinforcement Learning for BBU Placement and Routing in C-RAN
+21 more
← Authored by 29
5G infrastructures supporting end-user and operational services: The 5G-XHaul architectural perspective,
ANN-Based Multi-Channel QoT-Prediction Over a 563.4-km Field-Trial Testbed,
A Novel Autonomous Profiling Method for the Next-Generation NFV Orchestrators,
Auto-3P: An autonomous VNF performance prediction & placement framework based on machine learning,
Coexistence of Quantum and 1.6 Tbit/s Classical Data Over Fibre-Wireless-Fibre Terminals,
Deep Reinforcement Learning-Based Policy for Baseband Function Placement and Routing of RAN in 5G and Beyond,
Deep-reinforcement-learning-based RMSCA for space division multiplexing networks with multi-core fibers [Invited Tutorial],
Deep Reinforcement Learning for BBU Placement and Routing in C-RAN
+21 more
Affiliated with 3
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Summary
Dimitra Simeonidou worked as an engineer[1].
FAQs
What did Dimitra Simeonidou do for work?
Dimitra Simeonidou worked as engineer[1].
Where did Dimitra Simeonidou go to school?
Dimitra Simeonidou was educated at University of Essex[4].
What awards did Dimitra Simeonidou receive?
Honors received include Fellow of the Royal Academy of Engineering[5].