Benjamin Jin
Thesis title: Development of a machine learning method to automatically quantify calcified intracranial atheroma on CT imaging and assess risk of future neurovascular disease in a national dataset
Precision Medicine Doctoral Training Programme
Year of study: 2
Contact details
- Email: b.jin@ed.ac.uk
PhD supervisors:
Address
- Street
-
Centre for Clinical Brain Sciences
The Chancellor's Building
49 Little France Crescent - City
- Edinburgh
- Post code
- EH16 4SB
Background
I am a trained computer scientist investigating the early risk assessment of neurovascular disease from routine medical imaging for a PhD in Precision Medicine.
Between 2016 and 2022, I completed bachelor's and master's degrees in computer science at the University of Augsburg in Germany. During my studies, I worked on a project at a medium-sized company, developing models to predict solar power production based on weather forecasts and cloud movement. Additionally, I was a research assistant at the Chair of Embedded Intelligence for Health and Wellbeing. From 2022 to 2023, I contributed to a federally funded startup on conversational AI. I moved to the UK in 2023 to start my Precision Medicine Doctoral Training Programme at the University of Edinburgh.
Qualifications
- MSc in Computer Science, University of Augsburg, Germany (2022)
- BSc in Computer Science, University of Augsburg, Germany (2019)
Research summary
Deep learning for computer vision in combination with clinical data to assess risk of future neurovascular disease.