Shayan Mostafaei

About me

Overview

I am a Bioinformatician at the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, with a PhD in Biostatistics and Bioinformatics and postdoctoral training in Machine Learning, Artificial Intelligence, and dementia research.

My research lies at the intersection of bioinformatics, biostatistics, statistical genetics, multi-omics, artificial intelligence, and molecular epidemiology. I develop and apply advanced statistical and computational methods to large-scale population cohorts, health registries, and high-dimensional molecular data to better understand biological aging, dementia, age-related diseases, and individual variation in disease risk.

A major focus of my work is the integration of genetic, epigenetic, proteomic, metabolomic, clinical, and longitudinal data using machine learning and statistical modelling. My methodological interests include deep learning, generative and representation-learning approaches, statistical learning for omics data, polygenic risk prediction, Bayesian modelling, causal inference, survival analysis, longitudinal modelling, and interpretable risk prediction.

My recent research includes AI-based polygenic risk prediction for Alzheimer's disease and related dementias, biological aging and epigenetic aging, multi-omics aging signatures, and machine-learning methods for high-dimensional longitudinal and epidemiological data. I am particularly interested in developing reproducible and clinically relevant computational approaches that bridge molecular data, population health, and precision medicine.

Education

• PhD in Biostatistics and Bioinformatics, Tehran University of Medical Sciences, Tehran, Iran, 2018.

  Postdoctoral Training

• Postdoctoral Researcher in Machine Learning and Artificial Intelligence, School of Electrical Engineering and Computer Science, Department of Intelligent Systems, Division of Information Science and Engineering, KTH Royal Institute of Technology, Stockholm, Sweden, 2022.
• Postdoctoral Researcher in Dementia and Machine Learning, Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden, 2023.

• Artificial intelligence and machine learning in biomedicine
• Generative and representation learning
• Statistical learning for multi-omics data
• Bioinformatics and statistical genetics
• Multi-omics integration
• Biological aging and aging clocks
• Dementia and Alzheimer's disease and related dementias
• Polygenic risk prediction and genetic risk modelling
• GWAS and EWAS
• Survival, longitudinal, and risk modelling
• Bayesian modelling and causal inference
• Precision medicine and individualized risk prediction
• Large-scale population and registry-based data analysis
• High-dimensional biomedical data