Chrysostomos Symvoulidis

Affiliation Research Associate
TitlePostdoctoral Researcher
ExpertiseCausal Discovery, Causal Inference, Causal Learning, Cloud Computing, Complex Event Processing, Deep Learning, Edge Computing, Machine Learning

Short CV

Chrysostomos Symvoulidis, PhD is a Researcher at the University of Piraeus, Greece (Department of Digital Systems). He received his BSc in Digital Systems in 2016 and MSc in Big Data and Analytics in 2016, both from the Department of Digital Systems at the University of Piraeus. Since 2024, he holds a PhD from the University of Piraeus (Department of Digital Systems) in the field of Artificial Intelligence, with focus on causal and contextual information extraction and data enrichment methods with emphasis on artificial intelligence-driven optimization algorithms for Cloud and Edge Computing. His general research interests lie with issues related to causal discovery, causal inference, causal learning, cloud computing, edge computing, as well as machine learning and deep learning. In this context, he has participated in several EU and National funded projects (e.g., MATILDA, BigDataStack, InteropEHRate), leading research for addressing issues related to data analysis, Health Information Exchange, Complex Event Processing, as well as Cloud and Edge Computing orchestration using causally- and contextually-enhanced ML/DL methods, while he has also contributed in the aforementioned fields through multiple international conference and international journal publications.

Personal Research Topics

Cloud and Edge Computing orchestration

Causal and contextual information extraction and data enrichment methods with emphasis on artificial intelligence-driven optimization algorithms for Cloud and Edge Computing.

Dynamic Complex Event Processing (CEP) system using Machine Learning methods for optimal 5G-enabled services deployment

A complex event processing engine (CEP), enriched with Machine Learning capabilities, so that it is fully adapted to its environment, as a solution for monitoring component applications running on 5G infrastructure. The mechanism uses the Incremental DBSCAN algorithm to determine the normal behavior of developing services and to adapt accordingly.

Research Projects

  1. MATILDA
  2. InteropEHRate
  3. BIGDATASTACK

Scientific Publications

Journal Articles

  1. Symvoulidis, C., Kiourtis, A., Marinos, G., Totow Tom-Ata, J. D., Manias, G., Mavrogiorgou, A., Kyriazis, D. (2023, September) A User Mobility-based Data Placement Strategy in a Hybrid Cloud / Edge Environment using a Causal-aware Deep Learning Network, in IEEE Transactions on Computers, doi: 10.1109/TC.2023.3311921.
  2. Manias, G., Mavrogiorgou, A., Kiourtis, A., Symvoulidis, C., & Kyriazis, D. (2023, May) Multilingual text categorization and sentiment analysis: a comparative analysis of the utilization of multilingual approaches for classifying twitter data. In Neural Computing and Applications, Springer.
  3. Kiourtis, A., Giannetsos, A., Menesidou, S.A., Mavrogiorgou, A., Symvoulidis, C.,Graziani, A., Kleftakis, S., Mavrogiorgos, K., Zafeiropoulos, K.,Gkolias, C. A., Kyriazis, D. (2023, June) Identity management standards: A literature review. In Computers and Informatics.
  4. Mavrogiorgou, A., Kiourtis, A., Manias, G., Symvoulidis, C., & Kyriazis, D. (2023, February), Batch and Streaming Data Ingestion towards Creating Holistic Health Records, In Emerging Science Journal, pp.339-353.
  5. Lazic I., Agullo F., Ausso S., Alves B., Barelle C., Berral JL., Bizopoulos P., Bunduc O., Chouvarda I., Dominguez D., Filos D., Gutierrez-Torre A., Hesso I., Jakovljević N., Kayyali R., Kogut-Czarkowska M., Kosvyra A., Lalas A., Lavdaniti M., Loncar-Turukalo T., Martinez-Alabart S., Michas N., Nabhani-Gebara S., Raptopoulos A., Roussakis Y., Stalika E., Symvoulidis C., Tsave O., Votis K., Charalambous A. (2022, August).The Holistic Perspective of the INCISIVE Project—Artificial Intelligence in Screening Mammography. In Applied Sciences Journal, MDPI.
  6. Symvoulidis, C., Marinos, G., Kiourtis, A., Mavrogiorgou, A., Kyriazis, D. (2022, April). HealthFetch: An Influence-Based, Context-Aware Prefetch Scheme in Citizen-Centered Health Storage Clouds, In Future Internet Journal, MDPI.

Conference Articles

  1. Paraskevoulakou, E., Totow Tom-Ata, J.D., Symvoulidis, C., Kyriazis, D. (2024, January) Enhancing Cloud-Based Application Component Placement with AI-Driven Operations, in 2024 IEEE 14th Annual Computing and Communication Workshop and Conference (CCWC), IEEE.
  2. Kiourtis, A., Mavrogiorgou, A., Makridis, G., Symvoulidis, C., Mavrogiorgos, K., Kyriazis, D. (2023, November) A Practical Guide to Green Computing for Manufacturers, Businesses, and Individuals, in 2023 34th Conference of the Open Innovations Association (FRUCT).
  3. Symvoulidis, C., Kiourtis, A., Mavrogiorgou, A., Totow Tom-Ata, J. D., Manias, G., Kyriazis, D. (2023, October) Dynamic deployment prediction and configuration in hybrid cloud / edge computing environments using influence-based learning, in 2023 10th IEEE International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), doi: 10.1109/EECSI59885.2023.10295768, IEEE.
  4. Marinos, G., Symvoulidis, C., & Kyriazis, D. (2023, January). K-Medoids-Surv: A Patients Risk Stratification Algorithm Considering Censored Data, In 21st International Conference on Artificial Intelligence and Soft Computing (ICAISC 2022). Springer.
  5. Kiourtis, A., Mavrogiorgou A., Mavrogiorgos K., Kyriazis D., Graziani A., Symvoulidis C., Bella G., Bocca S., Torelli F. (2022, November). Electronic Health Records at People’s Hands Across Europe: The InteropEHRate Protocols. In pHealth 2022, pp. 145-150. IOS Press.
  6. Dimopoulou, S., Symvoulidis, C., Koutsoukos, K., Kiourtis A., Mavrogiorgou, A., Kyriazis, D. (2022, March). Mobile Anonymization and Pseudonymization of Structured Health Data for Research, In 2022 Seventh International Conference On Mobile And Secure Services (MobiSecServ) (pp. 1-6), IEEE.
  7. Koutsoukos, K., Symvoulidis, C., S., Kiourtis A., Mavrogiorgou, A., Dimopoulou, Kyriazis, D. (2022, February). Emergency Health Protocols Supporting Health Data Exchange, Cloud Storage, and Indexing, In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies – HEALTHINF (pp. 597-604).
  8. Marinos, G., Symvoulidis, C., & Kyriazis, D. (2021, December). MICSurv: Medical Image Clustering for Survival risk group identification, In 2021 4th International Conference on Bio-Engineering for Smart Technologies (BioSMART) (pp. 1-4), IEEE.
  9. Kiourtis, A., Graziani, A., Mavrogiorgou, A., Symvoulidis, C., Mavrogiorgos, K., & Kyriazis, D. (2021, December), A Health Information Exchange Protocol Supporting Bluetooth-based Messages, In 2021 International Conference on Information Systems and Advanced Technologies (ICISAT) (pp. 1-6), IEEE.
  10. Symvoulidis C., Mavrogiorgou A., Kiourtis A., Marinos G., & Kyriazis D. (2021, December), Facilitating Health Information Exchange in Medical Emergencies, In 2021 International Conference on e-Health and Bioengineering (EHB), IEEE.
  11. Symvoulidis, C., Kiourtis, A., Mavrogiorgou, A., & Kyriazis, D. (2021), Healthcare Provision in the Cloud: An EHR Object Store-based Cloud Used for Emergency.
  12. Kiourtis, A., Mavrogiorgou, A., Symvoulidis, C., Tsigkounis, C., & Kyriazis, D. (2021, February), Indexing of Cloud Stored Electronic Health Records for Consented Third Party Accessing, In 28th Conference of the Open Innovations Association (FRUCT), pp. 158-166, IEEE.
  13. Tsoumas, I., Symvoulidis, C., & Kyriazis, D. (2020, September), Learning a generalized matrix from multi-graphs topologies towards microservices recommendations, In Proceedings of SAI Intelligent Systems Conference (pp. 693-702), Springer, Cham.
  14. Tsoumas, I., Symvoulidis, C., Kyriazis, D., Gouvas, P., Zafeiropoulos, A., Melian, J., & Sterle, J. (2019, December), Modelling 5G Cloud-Native Applications by Exploiting the Service Mesh Paradigm, In European, Mediterranean, and Middle Eastern Conference on Information Systems (pp. 151-162), Springer, Cham.
  15. Symvoulidis, C., Tsoumas, I., & Kyriazis, D. (2019, July), Towards the identification of context in 5G infrastructures, In Intelligent Computing-Proceedings of the Computing Conference (pp. 406-418), Springer, Cham.
  16. Touloupou, M., Kapassa, E., Symvoulidis, C., Stavrianos, P., & Kyriazis, D. (2019, February), An integrated SLA management framework in a 5G environment, In 2019 22nd Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN) (pp. 233-235), IEEE.
  17. Mavrogiorgou, A., Kiourtis, A., Symvoulidis, C., & Kyriazis, D. (2018, October), Capturing the reliability of unknown devices in the IoT world, In 2018 Fifth International Conference on Internet of Things: Systems, Management and Security (pp. 62-69), IEEE.