Athanasios Tsanas ('Thanasis')
Chair (Full Professor) in Digital Health and Data Science
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 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, where he now holds the Chair (Full Professor) in Digital Health and Data Science. 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), and the BIOSTEC/Biosignals Best paper award (2021). He is Co-founder of the NHS Digital Academy, where he led the development and delivery of the 'Clinical Decision Support and Actionable Data Analytics' theme (2018-2022). 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 was funded through the AUKCAR renewal award.
Since 1st June 2023 she has started on a prestigious, 5-year tenure-track Chancellor's Fellowship with the Usher Institute, and is affiliated with DARTH.
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 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).
Awards during PhD:
First prize, Edinburgh Research Interest Group in Parkinson's (outreach event)
Katherine studied Applied Mathematics at Brown University (USA) and completed an MSc in Computational Applied Mathematics at the University of Edinburgh. Her MSc thesis focused on actigraphy data analysis for stroke patients which she completed within the DARTH group. Katherine had previously worked as a counselor at a summer youth camp and had taught English as a foreign language in Germany.
Her PhD focuses on using advanced data analytics and the use of wearable sensors to provide new insights into endometriosis.
Funding: Katherine is on a full 3-year scholarship covering fees+stipend from Standard Life + University of Edinburgh top-up.
Craig comes from a background of clinical medicine at the University of Edinburgh where he completed his medical degree (MBChB 2018) and a BSc Hons in Physiology (2015). Following his foundation training as a doctor he has completed a Masters in Biomedical Artificial Intelligence (MSC (R) 2021) as part of the Biomedical AI CDT which continues into a 3 year PhD.
His research is focused on the potential for AI and machine learning methods to aid in clinical decision making, particularly using physiological data. He is currently focused on developing predictive models for optimising organ donation in intensive care environments using physiological and clinical data.
Funding: Craig is funded through the UKRI CDT Biomedical AI with a 4-year studentship, covering tuition fees, stipend and travel/research support.
Shuo studied Economics and Computer Science during her bachelor's degree (2019) and completed an MSc in Statistics with Data Science at the University of Edinburgh (2020). She has worked as a research assistant for Tsinghua University, specializing in extracting dietary patterns via analysis of social media platform data (2021-2022). Her main work involved exploring links between boosts in sodium content in accessed recipes from social media over time with time series of hospital admissions for chronic illness. The experience intrigued her to explore more in the interdisciplinary field related to healthcare.
Her PhD research focuses on preventing rehospitalizations of elderly acute care survivors using longitudinal physical and mental health monitoring with wearable sensors and smartphones. Shuo is co-supervised by Prof. Tim Walsh.
Funding: Shuo is funded through the Dunhill Medical Trust PhD studentships. (full 4-year scholarship covering fees+stipend)."
Edward T. Chiyaka
MSc student in Data Science, Technology & Innovation
Edward studied Mathematics for his undergraduate and MSc degrees and completed a PhD in Public Health at Kent State University, USA (2019). He is currently an Assistant Professor of Healthcare Administration and Research in the Wingate University School of Pharmacy.
Edward has research interests in health outcomes, care coordination, digital health, health systems, and prevention science. He is enrolled in the MSc in Data Science, Technology & Innovation (School of Informatics, University of Edinburgh).
His research is focused on identifying factors associated with asthma severity and predicting the progression of the disease.
Edward is co-supervised by Thanasis and Holly.