Journals 

  1. Miedema, R., & Strydis, C. (2024). ExaFlexHH: an exascale-ready, flexible multi-FPGA library for biologically plausible brain simulations. Frontiers in Neuroinformatics, 18, 1330875. 
  2. Landsmeer, L. P., Engelen, M. C., Miedema, R., & Strydis, C. (2024). Tricking AI chips into simulating the human brain: A detailed performance analysis. Neurocomputing, 127953. 
  3. De Ridder, D., Siddiqi, M. A., Dauwels, J., Serdijn, W. A., & Strydis, C. (2024). NeuroDots: From Single-Target to Brain-Network Modulation: Why and What Is Needed?. Neuromodulation: Technology at the Neural Interface.
  4. Kromes, R., Li, T., Bouillon, M., Güler, T. E., van der Hulst, V., & Erkin, Z. (2024). Fear of Missing Out: Constrained Trial of Blockchain in Supply Chain. Sensors, 24(3), 986.
  5. Messinis, S., Temenos, N., Protonotarios, N. E., Rallis, I., Kalogeras, D., & Doulamis, N. (2024). Enhancing Internet of Medical Things security with artificial intelligence: A comprehensive review. Computers in Biology and Medicine, 108036.

Conferences

 

  1. Siddiqi, M. A., Vrijenhoek, D., Landsmeer, L. P., van der Kleij, J., Gebregiorgis, A., Romano, V., … & Strydis, C. (2023). A Lightweight Architecture for Real-Time Neuronal-Spike Classification. arXiv preprint arXiv:2311.04808.
  2. Khaled, A. A., Hasan, M. M., Islam, S., Papastergiou, S., & Mouratidis, H. (2024, June). Synthetic Data Generation and Impact Analysis of Machine Learning Models for Enhanced Credit Card Fraud Detection. In IFIP International Conference on Artificial Intelligence Applications and Innovations (pp. 362-374). Cham: Springer Nature Switzerland.
  3. Basheer, N., Pranggono, B., Islam, S., Papastergiou, S., & Mouratidis, H. (2024, June). Enhancing Malware Detection Through Machine Learning Using XAI with SHAP Framework. In IFIP International Conference on Artificial Intelligence Applications and Innovations (pp. 316-329). Cham: Springer Nature Switzerland.
  4. Betting, J. L. F., De Zeeuw, C. I., & Strydis, C. (2023, December). Oikonomos-II: A Reinforcement-Learning, Resource-Recommendation System for Cloud HPC. In 2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics (HiPC) (pp. 266-276). IEEE.
  5. Siddiqi, M. A., Hernández, J. A. G., Gebreziorgis, A., Bishnoi, R., Strydis, C., Hamdioui, S., & Taouil, M. (2023, September). Memristor-Based Lightweight Encryption. In 2023 26th Euromicro Conference on Digital System Design (DSD) (pp. 634-641). IEEE.
  6. Messinis, S., Protonotarios, N., Tzortzis, I., Rallis, I., Kalogeras, D., & Doulamis, N. (2023, July). Lightweight machine learning for privacy-preserving and secure networked medical devices: The SEPTON project use cases. In Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 638-644).
  7. Arapidis, E., Temenos, N., Giagkos, D., Rallis, I., Kalogeras, D., Papadakis, N., … & C. Messinis, S. (2024, June). Zeekflow+: A Deep LSTM Autoencoder with Integrated Random Forest Classifier for Binary and Multi-class Classification in Network Traffic Data. In Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 613-618).
  8. Ioannidis, A., Litke, A., & Papadakis, N. (2024, June). Randomized Response and Differential Privacy. In Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 600-605).
  9. Koulianos, A., Paraskevopoulos, P., Litke, A., & Papadakis, N. (2024, June). Towards Enhanced Data Integrity and Accountability: Leveraging Blockchain Technology in Healthcare. In Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 587-592).
  10. Bakiris, E., Papadakis, N., Katsarou, V., & Alampasis, N. (2024, June). SEPTON Toolkit application: An overview of the security techniques used from wearable medical devices to physician’s healthcare platform. In Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 582-586).
  11. C. Messinis, S., Ε. Protonotarios, N., Arapidis, E., & Doulamis, N. (2024, June). Client Selection and Resource Allocation via Graph Neural Networks for Efficient Federated Learning in Healthcare Environments. In Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 606-612).
  12. Taylor, S., Gilje Jaatun, M., Bernsmed, K., Androutsos, C., Frey, D., Favrin, S., … & Katzis, K. (2024, June). A Way Forward for the MDCG 2019-16 Medical Device Security Guidance. In Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 593-599).
  13. Khattat, M., & Kromes, R. (2024, May 27). Completely FROST-ed: IoT issued FROST signature for Hyperledger Fabric blockchain. IEEE International Conference on Blockchain and Cryptocurrency (IEEE ICBC), Trinity College Dublin, Ireland. https://doi.org/10.5281/zenodo.12683374.