Chair of Information Theory and Data Analytics Ahmad Ayad, M.Sc.
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ahmad.ayad"at"inda.rwth-aachen.de |
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Research Interest
My research interests include:
- Modelling medical processes using machine learning tools and creating pipelines for products to be used in critical care.
- Combining state of the art technologies with Internet of thigns networks to achieve more robust, secure and efficient communications.
- Enhancing security of IoT networks using machine learning.
- Anomaly detection in IoT networks and medical data.
- Distributed ledger technology in IoT networks.
Open Positions
Please contact me directly if you are interested in doing a master/bachelor thesis in one of the topics mentioned above.
Short Curriculum Vitae
| 02/2019 - Present | Research and teaching assistant, RWTH Aachen University, Germany. |
| 11/2016 - 01/2019 | Telecommunications Intern, Telefonica, Germany. |
| 09/2016 - 11/2018 | M.Sc. Communications Engineering, RWTH Aachen University, Germany. |
| 05/2015 - 08/2016 | Telecommunications Engineer, Dar Al-Handasah, Jordan. |
| 01/2015 - 04/2015 | Software Developer, TechnoEcho, Jordan. |
| 09/2013 - 09/2016 | B.Sc. Electrical Engineering University of Jordan, Jordan. |
Publications
- A. Ayad, M. Barhoush, J. Loh, T. Gemmeke, A. Schmeink, "PEACE: Private and Energy-efficient Algorithm for Cardiac Evaluation on the EDGE using Modified Split Learning and Model Quantization", IEEE Int. Conf. on Inf. and Comm. Sys., Sep 2023, accepted.
- M. Kohankhaki, A. Ayad, M. Barhoush, A. Schmeink, "Detecting Data Poisoning in Split Learning Using Intraclass-Distance Inflated Loss", IEEE GLOBECOM Workshop, 2023, accepted.
- A. Ayad, M. Barhoush, M. Frei, B. Völker and A. Schmeink, "An Efficient and Private ECG Classification System Using Split and Semi-Supervised Learning," in IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 9, pp. 4261-4272, Sept. 2023.
- M. Barhoush, A. Ayad, A. Schmeink, "Accelerating Federated Learning via Modified Local Model Update Based on Individual Performance Metric", ICECCME, 2023, accepted.
- M. Barhoush, A. Ayad and A. Schmeink, "Semi-supervised Learning in Distributed Split Learning Architecture and IoT Applications," 2023 IEEE 15th International Symposium on Autonomous Decentralized System (ISADS), Mexico City, Mexico, 2023, pp. 1-6
- M. Barhoush, A. Ayad and A. Schmeink, "Semi-supervised Algorithms in Resource-constrained Edge Devices: An Overview and Experimental Comparison," 2022 IEEE iThings and IEEE GreenCom and IEEE CPSCom and IEEE SmartData and IEEE Cybermatics, Espoo, Finland, 2022, pp. 555-559.
- M. Kohankhaki, A. Ayad, M. Barhoush, B. Leibe, A. Schmeink, "Radiopaths: Deep Multimodal Analysis on Chest Radiographs," IEEE International Conference on Big Data Workshop (MMBD), 2022, accepted.
- A. Ayad, A. Hallawa, A. Peine, L. Martin, L. B. Fazlic, G. Dartmann, G. Marx, A. Schmeink, "Predicting Abnormalities in Laboratory Values of Patients in the Intensive Care Unit Using Different Deep Learning Models: Comparative Study," Journal of Medical Internet Research (JMIR) Medical Informatics, 2022;10(8):e37658 [ Link ]
- A. Ayad, J. Borsch and A. Schmeink, "Communication and Service Aspects of Smart Mobility: Improving Security, Privacy and Efficiency of Mobility Services by Utilizing Distributed Ledger Technology," Book chapter in Smart Transportation: AI Enabled Mobility and Autonomous Driving, CRC Press, Taylor & Francis, to appear Aug. 2021.
- A. Ayad, M. Frei, A. Schmeink, "Efficient and Private ECG Classification on the Edge Using a Modified Split Learning Mechanism," 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI), Rochester, MN, USA, 2022, pp. 01-06,
- A. Ayad, M. Renner, A. Schmeink, "Improving the Communication and Computation Efficiency of Split Learning for IoT Applications", Globecom SAC MLC, 2021.
- A. Ayad, A. Zamani, A. Schmeink, G. Dartmann, "Design and Implementation of a Hybrid Anomaly Detection System for IoT", Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS), Oct 2019.
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