Deep Recurrent Neural Networks for Human Activity Recognition. - Abdulmajid Murad; Jae-Young Pyun (Sensors, 2017)

IoT Sensor Gym: Training Autonomous IoT Devices with Deep Reinforcement Learning. - Abdulmajid Murad; Kerstin Bach; Frank Alexander Kraemer; Gavin Taylor (IOT, 2019)

Autonomous Management of Energy-Harvesting IoT Nodes Using Deep Reinforcement Learning. - Abdulmajid Murad; Frank Alexander Kraemer; Kerstin Bach; Gavin Taylor (SASO, 2019)

Information-driven adaptive sensing based on deep reinforcement learning. - Abdulmajid Murad; Frank Alexander Kraemer; Kerstin Bach; Gavin Taylor (IOT, 2020)

Learning Task Agnostic Skills with Data-driven Guidance. - Even Klemsdal; Sverre Herland; Abdulmajid Murad (CoRR, 2021)

Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting. - Abdulmajid Murad; Frank Alexander Kraemer; Kerstin Bach; Gavin Taylor (Sensors, 2021)

Uncertainty-Aware Autonomous Sensing with Deep Reinforcement Learnings. - Abdulmajid Murad (2023)

Uncertainty-aware autonomous sensing with deep reinforcement learning. - Abdulmajid Murad; Frank Alexander Kraemer; Kerstin Bach; Gavin Taylor (Future Gener. Comput. Syst., 2024)

Synthetic Aircraft Trajectory Generation Using Time-Based VQ-VAE. - Abdulmajid Murad; Massimiliano Ruocco (CoRR, 2025)

PIGPVAE: physics-informed gaussian process variational autoencoders. - Michail Spitieris; Massimiliano Ruocco; Abdulmajid Murad; Alessandro Nocente (Appl. Intell., 2025)

Pre-Tactical Flight-Delay and Turnaround Forecasting with Synthetic Aviation Data. - Abdulmajid Murad; Massimiliano Ruocco (CoRR, 2025)