Experience

Continuing research collaboration on federated learning and edge AI following PhD completion. Working on ongoing publications and EU project deliverables.

Leading research in federated learning, trustworthy AI, and human-environment technology at MRU's HET department. Teaching, supervision, and research grant activities.

Collaborative research on federated learning for edge computing environments. Delivered guest lectures on privacy-preserving machine learning and co-authored research publications.

Short-term research visit for collaborative work on communication-efficient federated learning.

Contributed to research on AI applications in biomechanics. Developed machine learning models for biomedical signal processing and collaborated on interdisciplinary publications. Project end: 31-Aug-2023.

Remote research on distributed machine learning systems. Participated in research seminars and established international research collaborations.

Thesis: Enhancing Communication-Efficient Federated Learning for Human Activity Recognition through Highly Compressed Models