Presentation

I am an Applied Data Science M.Sc. graduate from Malmö University with a Computer Science background and experience in machine learning, biomedical AI, wearable systems, and large-scale sensor data processing.

My skills include deep learning, time-series analysis, medical image analysis, multimodal learning, model interpretability, Python, PyTorch, C/C++, SQL, Docker, Git, and GPU/HPC-based experimentation.

My recent work focuses on interpretable AI for ECG-based seizure prediction, including CNN, attention-based, and prototype-based models. I am also interested in biomedical AI, precision medicine, multi-omics integration, and clinical decision-support systems.

My research environments

Perspectives on Social Health – POSH

Perspectives on Social Health (POSH) focus on social health, which has an impact on both physical and mental health. We...

Sustainable Digitalisation Research Centre

The research centre studies both social and technological aspects to promote sustainable digitalisation. The aim is to...