Join My Research

I supervise and collaborate on deep-learning research at the Faculty of Computing and Informatics, Multimedia University (MMU). If you are a prospective research assistant or an MSc / PhD applicant interested in any of the topics below — or a related idea of your own — email me with a short introduction, your CV, and the topic you want to work on.

Open research topics

7 topics currently open · all related to deep learning

1. Deep learning for IoT malware behavior detection

   Behavioral fingerprinting of malware in cloud–IoT environments using deep sequence models. Builds directly on our published detection-and-containment framework and its open replication package.

   I'm interested →
2. Federated deep learning for privacy-preserving analytics

   Training deep models across distributed devices without centralizing raw data — aggregation strategies, non-IID data, and communication-efficient updates.

   I'm interested →
3. Metaheuristic optimization of deep neural networks

   Using Ant Colony Optimization and other metaheuristics for hyperparameter tuning and neural architecture search, connecting classic swarm intelligence to modern deep learning.

   I'm interested →
4. Lightweight deep learning for edge devices

   Model compression, pruning, and quantization so deep networks run on resource-constrained IoT and mobile hardware without losing accuracy.

   I'm interested →
5. Deep learning for network intrusion detection

   Anomaly-based intrusion detection with recurrent and transformer architectures, evaluated on modern benchmark datasets and real traffic.

   I'm interested →
6. Deep reinforcement learning for cloud resource scheduling

   Learning task-scheduling and resource-allocation policies for cloud and grid computing, benchmarked against metaheuristic schedulers.

   I'm interested →
7. Explainable deep learning (XAI)

   Interpretability methods that make deep-model decisions auditable in security- and safety-critical settings.

   I'm interested →