Associate Prof. (tenured)
Thanasis studied Engineering for his undergraduate and MSc degrees and completed a PhD in Applied Mathematics at the University of Oxford (2012). He continued working at the University of Oxford as a Research Fellow in Biomedical Engineering and Applied Mathematics (2012-2016), Stipendiary Lecturer in Engineering Science (2014-2016), and Lecturer in Statistical Research Methods (2016-2019). He joined the Usher Institute, Edinburgh Medical School, University of Edinburgh in January 2017 on a prestigious tenure-track Chancellor's Fellowship. He secured tenure a year early (December 2019) and was promoted to Associate Professor in Data Science (May 2020). He is Director of Knowledge Exchange and Research Impact at the Usher Institute, and Co-Director of Telescot.
He received the Andrew Goudie award (top PhD student across all disciplines, St. Cross College, University of Oxford, 2011), the EPSRC Doctoral Prize award (2012) as one of only 8 Oxford PhD students across 11 departments, the young scientist award (MAVEBA, 2013), the EPSRC Statistics and Machine Learning award (2015), the BIOSTEC/Biosignals Best paper award (2021). He is Co-founder of the NHS Digital Academy, where he leads the development and delivery of the 'Clinical Decision Support and Actionable Data Analytics' theme. He sits on the Editorial Boards of JMIR Mental Health and JMIR mHealth and uHealth. He is a Senior Member of IEEE, a Fellow of the Higher Education Academy, and a Fellow of the Royal Society of Medicine.
Holly studied Mathematics at the University of Cardiff and has an MPhil in Epidemiology from the University of Cambridge. She has completed her PhD with the DARTH group, co-supervised by Prof. Aziz Sheikh and Thanasis. Prior to joining DARTH she was a research fellow in Statistics at the University of Melbourne, and an Assistant Statistician at Roche.
Holly's post-doctoral work is funded through the AUKCAR renewal award.
Dorien is a clinical epidemiologist who had previously studied at the Leiden University (BSc), the University of Amsterdam (MSc), and the Maastricht University (PhD). She has considerable experience in healthcare settings, having worked as a clinical perfusionist for almost 6 years. Before joining the group she was a visiting researcher at the University of Edinburgh for 6 months.
Elsie comes from a Mathematics background from the University of Bristol, and has completed an MSc in Medical Statistics at the University of Leicester. She was a research assistant through a pre-doctoral research methods fellowship at the University of Bristol before joining DARTH.
Her work is focused on mining electronic health records to better understand disease subtypes in asthma. She is affiliated with the AUKCAR and is co-supervised by Prof. Aziz Sheikh. Elsie completed a 6-month internship in mathematical modeling at Roche Pharmaceuticals in Basel, Switzerland (September 2019 - February 2020) during her 3rd PhD year.
Funding: Elsie is fully funded through Farr (full 3-year scholarship covering fees+stipend).
Awards during PhD:
Best lighting talk, AUKCAR (March 2020)
2nd place PhD thesis competition, Medical School, University of Edinburgh
Dimitrios studied Statistics at the Athens University of Economics and Business, and completed an MSc in Medical Statistics at the University of Southampton (2018). He has also completed an online micro-Masters program in Data Science offered by the University of California San Diego. He had previously worked as a Data Analyst at Predicta S.A.
He is working on the characterization of myocardial infarction using statistical machine learning algorithms capitalizing on routinely collected data in cardiovascular clinical practice. Dimitrios is affiliated with both the Usher Institute of Population Health Sciences and Informatics and the Centre for Cardiovascular Science and is co-supervised by Prof. Nick Mills.
Funding: Dimitrios is funded through the Medical Research Council (MRC) DTP Precision Medicine programme (full 3.5-year scholarship covering fees+stipend).
Filip comes from a Computing background (Zagreb, Croatia), and has completed an MSc in Artificial Intelligence at the University of Edinburgh (2018). He has been passionate about computers since his childhood years.
His research focuses on developing novel and applying existing machine learning approaches to healthcare, in an effort to improve patient diagnosis and recovery. He is currently focused on clustering and feature selection techniques to tackle myocardial infarction. Filip is affiliated with both the Usher Institute of Population Health Sciences and Informatics and the Centre for Cardiovascular Science and is co-supervised by Prof. Nick Mills.
Funding: Filip is a British Heart Foundation (BHF) funded research student on the BHF PhD programme in Cardiovascular Science at the University of Edinburgh (full 3-year scholarship covering fees+stipend).
Evi has completed her medical training (MBBS) at the Aristotle University of Thessaloniki, and has an MSc in Data analytics from the same university. In both her degrees she graduated as top student of her class. She has worked as an intern at the Chelsea and Westminster Hospital in London, specializing in paediatric gastroenterology. She has worked as a GP and towards her residency in Paediatrics (ST1 equivalent) at the County General Hospital of Agios Nikolaos, Crete, Greece. She has also worked as an intern at the Children's hospital of Philadephia in the Immunogenetics and Transplantation laboratory in the USA.
She is working on neonatal monitoring and childhood development by mining a wide range of questionnaires and additional signal modalities including MRI. Evi is co-supervised by Prof. James Boardman, Dr Donald MacIntyre, and Dr Richard Chin.
Funding: CF funds from the University of Edinburgh (full 3-year scholarship covering fees+stipend).
Awards during PhD:
SPR MD/PhD Student Research Award at the Society for Pediatrics Research conference (one of the biggest international academic meetings in the area of Pediatrics) for her research paper: “Machine Learning for Stratification of children at risk of language delay following Preterm Birth", PAS conference (March 2021)
Andres obtained his degree in Electrical Engineer at the Universidad Politécnica de Madrid in 2016 (MSc. level). He spent the last year of his undergraduate programme as an Erasmus exchange student at the Technical University of Eindhoven, The Netherlands. During this period, he worked as an intern for Philips Research at the High Tech Campus. Before joining DARTH he had been with the research group of Signal and Image Processing at the Biomedical Technology Center (RGSIP-CTB) of Universidad Politécnica de Madrid (2016-2019). His main work involved the recording of speech and facial myoelectric surface signals in neuromotor degenerative disease for patients with cognitive diseases and language disorders.
Andres is working on speech signal processing algorithms applied to neurodegenerative disorders. He is co-supervised by Dr Saturnino Luz at Edinburgh, Prof. Victor Nieto Lluis (Universidad Polytecnica de Madrid) and Prof. Per Svenningson (Karolinska Institute).
Funding: Andres is funded through the Medical Research Council (MRC) DTP Precision Medicine programme (full 3.5-year scholarship covering fees+stipend).