Design and Implementation of a Hybrid Anomaly Detection System for IoT. - Ahmad Ayad; Alireza Zamani; Anke Schmeink; Guido Dartmann (IoTSMS, 2019)

Improving the Communication and Computation Efficiency of Split Learning for IoT Applications. - Ahmad Ayad; Melvin Renner; Anke Schmeink (GLOBECOM, 2021)

Radiopaths: Deep Multimodal Analysis on Chest Radiographs. - Mohammad Kohankhaki; Ahmad Ayad; Mahdi Barhoush; Bastian Leibe; Anke Schmeink (IEEE Big Data, 2022)

Efficient and Private ECG Classification on the Edge Using a Modified Split Learning Mechanism. - Ahmad Ayad; Marian Frei; Anke Schmeink (ICHI, 2022)

Detecting Data Poisoning in Split Learning Using Intraclass- Distance Inflated Loss. - Mohammad Kohankhaki; Ahmad Ayad; Mahdi Barhoush; Anke Schmeink (GLOBECOM (Workshops), 2023)

Energy Efficient ECG Classifier Using Smart Lead Switching and Apache TVM. - Ahmad Ayad; Mahdi Barhoush; Benedikt Völker; Steffen Leonhardt; Anke Schmeink (ICMLA, 2023)

Semi-supervised Learning in Distributed Split Learning Architecture and IoT Applications. - Mahdi Barhoush; Ahmad Ayad; Anke Schmeink (ISADS, 2023)

An Efficient and Private ECG Classification System Using Split and Semi-Supervised Learning. - Ahmad Ayad; Mahdi Barhoush; Marian Frei; Benedikt Völker; Anke Schmeink (IEEE J. Biomed. Health Informatics, 2023)

HypoTreat: Reducing Hypoglycemia in Artificial Pancreas Simulation. - Miriam Chlumsky-Harttmann; Ahmad Ayad; Anke Schmeink (EAIS, 2024)

Communication-efficient Decentralised Federated Learning via Low Huffman-coded Delta Quantization Scheme. - Mahdi Barhoush; Ahmad Ayad; Mohammad Kohankhaki; Anke Schmeink (IWCMC, 2024)

Smart Summary: A Distributed Medical Recommender System for Patients in the ICU Using Neural Networks. - Ahmad Ayad; Yu-Hsuan Tai; Guido Dartmann; Anke Schmeink (IEEE Access, 2024)

Parallel Split Learning with Global Sampling. - Mohammad Kohankhaki; Ahmad Ayad; Mahdi Barhoush; Anke Schmeink (CoRR, 2024)