Project Title: Towards the early diagnostic and identification of new drug targets for Parkinson’s Disease by digital tracking of early non-motor symptoms
Supervisor: Dr Cynthia Sandor
Location: Level 7, Sir Michael Uren Hub, White City Campus, 86 Wood Lane, W12 0BZ
About Me
I am a Research Assistant in Machine Learning and a PhD student in the Sandor Laboratory in the Department of Brain Sciences within the UK Dementia Research Institute Centre at Imperial College London. My project focuses on AI-driven drug repurposing and early biomarker discovery in Parkinson’s disease using electronic health records (EHR) and wearable data.
Specifically, I aim to identify non-Parkinson’s drugs that could have disease-modifying or protective effects by applying causal inference and machine learning to large-scale datasets like CPRD (Clinical Practice Research Datalink) and PPMI (Parkinson’s Progression Markers Initiative). Additionally, I work on detecting early non-motor symptoms of Parkinson’s disease—such as sleep disturbances, autonomic dysfunction, and psychological symptoms—from wearable and medical records to improve early diagnosis. The ultimate goal of my research is to enable earlier intervention and identify therapeutics that could alter disease progression before irreversible neurodegeneration occurs.
How did you become interested?
My academic journey has long been revolving around neuroscience and AI. After completing a BSc in Neuroscience at UCL and an MSc in Translational Neuroscience at Imperial, I became interested in computational methods for analysing neurophysiological data. My first MSc thesis focused on unsupervised learning for sleep fragmentation analysis using EEG.
Realizing my limitations in AI-driven methods, I pursued a second MSc in Artificial Intelligence at Imperial to strengthen my foundation in machine learning, mathematics, and coding. My MSc project applied AI-driven time-series analysis of EEG to predict sleep onset, reinforcing my passion for decoding neurophysiological signals.
After my MSc, I worked as a Research Assistant in Prof. Nir Grossman’s lab, developing and testing a methodology for predicting sleep onset using bifurcation dynamical system modelling of EEG dynamics. This approach leverages the criticality of transitions between sleep and wakefulness to detect tipping points that precede sleep onset.
The combination of these experiences deepened my interest in using AI for neurodegenerative disease research, particularly in leveraging temporal data from sensors and electronic healthcare records for early diagnostics and drug discovery, which led me to pursue this PhD.
What do you do in your spare time?
Outside of research, I am passionate about dancing, which I’ve been doing recreationally for a few years. I also enjoy running, yoga and going to the gym, as they help me maintain balance and mental clarity. When I’m not dancing or exercising, I love reading—whether it’s neuroscience, psychology, philosophy, classical literature, or good fiction—and exploring how neuroscience principles can be applied to productivity, health optimization, and AI research. As a creative outlet, I enjoy playing piano, jamming, and singing (badly)—even if my vocals are questionable, I love the freedom and expression that music brings.
Qualifications
Imperial College London
PhD in Artificial Intelligence and Clinical Neuroscience – Sep 2024 - Present
MSc in Artificial Intelligence (Distinction) – Oct 2022 - Oct 2023
MSc in Translational Neuroscience (Distinction) – Oct 2021 - Oct 2022
University College London
Bachelor of Science (BSc) in Neuroscience (First Class Honours) – Sep 2018 - Jun 2021
Research Interests
• AI-driven Drug Repurposing
• Early Biomarker Discovery for Neurodegenerative
• Causal Inference in Healthcare
• Neuroscience-inspired AI
• Time-series Analysis of Sensor Data
• Personalised Medicine & Digital Health
Presentations and Conferences
Connectome 2024 – ‘Identifying coincident drugs that alter Parkinson’s disease progression’
Outreach
• Imperial Tech Foresight Showcase:
4 June 2025 – PhD Speaker on Future of Parkinson’s Research: early detection through AI and technology and causal inference-based drug repurposing using electronic healthcare records.
• Great Exhibition Road Festival
15-16 June 2024 – Temporal Interference Stimulation Stand (Interventional Systems Neuroscience Lab)
7-8 June 2025 – AI-powered Digital Biomarkers for Parkinson’s Disease Stand (Sandor’s Lab)
• School’s Lectures/Workshops:
15 May 2024 – AI for medicine & Future of Healthcare speaker for Notting Hill and Ealing High School’s Healthcare conference
12 March 2025 – Neuroscience workshop at Archbishop Sumner Primary School for years 3-6 during British Science Week
Confronting Inequality in Education Tutoring Initiative:
I have been an active member of the Confronting Inequality in Education Committee and a tutor in this programme (more details here).
Contact Details
Email: anastasia.ilina21@imperial.ac.uk
Twitter: ilina2902
LinkedIn: anastasia-ilina-57ba46172
