Project title: Multi-modal Machine Learning for the Prediction and Clinical Stratification of Parkinson’s Disease
Supervisors: Dr Cynthia Sandor, Professor Payam Barnaghi, Professor Marina Botto
Location: Level 7, Sir Michael Uren Hub, White City Campus, 86 Wood Lane, W12 0BZ
About me
Marirena is currently pursuing a PhD in Clinical Medicine Research at Imperial College London, where her work focuses on developing and applying machine learning approaches to identify biomarkers for the early prediction of Parkinson’s Disease. She is also developing machine learning and deep learning approaches for representation learning to address disease stratification. Her research integrates clinical targeted proteomics (i.e., Olink and SomaLogic), electronic health record (EHR) data, and smartwatch-derived digital biomarkers to uncover new insights into Parkinson’s disease biology. Marirena also works as a Research Assistant in Machine Learning for Clinical Data Science at the UK Dementia Research Institute at Imperial. Her previous research focused on leveraging remote monitoring and in-home sensor data to develop tools for detecting and managing agitation episodes in patients with dementia.
Outside academia, Marirena enjoys spending time with her dog, Zizel, and taking her on long walks in the park. She loves swimming, traveling, and exploring global cultures.
Qualifications
Postgraduate Training
Presentations
- Poster at Connectome 2023 : An explainable machine learning approach leveraging sleep patterns and ambient light exposure
Selected Publications
Outreach
Contact Details
Email: marirena.bafaloukou22@imperial.ac.uk
LinkedIn: marirena-bafaloukou-269aa520a
