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Personal profile

My research in a nutshell

I develop and apply novel time-series, signal processing, pattern recognition, and statistical machine learning algorithms to provide insight into data and address unmet needs (primarily in the healthcare domain). My algorithms are directly driven by and validated on complicated real-world problems, providing insight and facilitating interpretation of the underlying key mechanisms of the modeled system. My work is inherently multi-disciplinary, collaborating with industrial partners and colleagues from diverse backgrounds worldwide.

Indicative applications include longtidutinal telemonitoring of chronic diseases, natural language processing, data fusion, multi-sensor processing, biomechanics, and betting strategy optimisation. 

Qualifications

BSc Biomedical Engineering, Technological Educational Institute of Athens, Greece

BEng Electrical Engineering and Electronics, University of Liverpool, UK

MSc Signal Processing and Communications, Newcastle University, UK

DPhil (PhD) Applied Mathematics, University of Oxford, UK

FHEA: Fellow, Higher Education Academy

Websites

Current Research Interests

Time-series analysis, signal processing, pattern recognition, and statistical machine learning algorithms, focusing on biomedical applications.

Indicative projects I am currently working on include longitudinal telemonitoring of chronic diseases using wearable devices (e.g. smartwatches) and smartphones, and speech signal processing applications.

Collaborative Activity

What do I do?

I’m an applied mathematician/engineer specializing broadly on data science, in particular time-series analysis, signal processing, and statistical machine learning. I develop and apply algorithms to explore data and decipher complicated concealed statistical relationships. My algorithms are directly driven by and validated on complicated real-world problems, aiming to facilitate interpretation of the underlying key mechanisms of the modelled system. For further information and indicative projects please see the Data Analytics Research and Technology (DARTH) group webpage: https://www.darth-group.com/.

What is the real world applicability of my research?

My work is applicable across a range of real-world settings from healthcare to finance, forensics, energy – essentially any domain that has generated data. I have worked primarily on biomedical applications; other applications I have worked on include optimization betting strategy optimization, energy performance requirements in buildings, forensic phonetics, statistical risk disclosure for dataset release etc.

How could this apply to commercial stakeholders?

I provide insights into problems when presented with data. I have a track record of advising partners/colleagues from data collection all the way to analysis and implementation. My research findings have been explored commercially (e.g. Intel Corporation, LSVT Global and others) and I have consulted for industrial partners worldwide including work with industrial partners in the UK, US, Switzerland, Australia, Spain, etc.

I have active collaborations with researchers worldwide. I have published papers/written grants with researchers based at the UK, USA, Australia, Spain, Greece, Italy, Chile, India.

Some of my collaborators are based at MIT, Stanford, University of Oxford, Polytecnica de Madrid, University of Melbourne.

Biography

I studied Engineering and completed a DPhil (PhD) in Applied Mathematics at the University of Oxford (2012). I worked 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). I joined the Usher InstituteEdinburgh Medical SchoolUniversity of Edinburgh in January 2017 on a prestigious 5-year tenure-track Chancellor's Fellow post. I secured tenure early (1 Dec. 2019) and was promoted to Associate Professor in Data Science in August 2020. Upon joining the University I founded and lead the Data Analytics Research and Technology in Healthcare (DARTH) group (https://www.darth-group.com/). I am Co-Director of Telescot (with Prof. Stewart Mercer), an academic programme focusing on telemedicine. I have Co-Founded and I am Theme Leader of the 'Clinical Decision Support and Actionable Data Analytics' module in the innovative £6m NHS Digital Academy leadership programme, the first national NHS health informatics training programme. 

I received the Andrew Goudie award (top PhD student across all disciplines, St. Cross College, University of Oxford, 2011), the EPSRC Doctoral Prize award (2012), the young scientist award (MAVEBA, 2013), the EPSRC Statistics and Machine Learning award (2015), and the BIOSTEC/Biosignals Best paper award (2021). I have reviewed work for more than 50 technical and clinical journals, and have won a ‘Best reviewer award’ from the IEEE Journal of Biomedical Health Informatics (2015), and an 'Outstanding reviewer' award from the journal Computers in Biology and Medicine. Recent work was highlighted as paper of the month by HDRUK (9/2019). My work on speech and Parkinson’s disease has been commercially explored by Intel Corporation and LSVT Global and has been featured in the media, including Reuters. I sit on the Editorial Boards of JMIR Mental Health and JMIR mHealth and uHealth. I am a Senior Member of IEEE, a Fellow of the Higher Education Academy, and a Fellow of the Royal Society of Medicine.

Outside academics, I am a keen chess player having been the Greek under-20s champion (2003) and having participated in European and World Chess Championships.

Teaching

I have taught undergraduate or graduate courses in the Engineering Science dept., the Mathematics dept., the Sleep and Circadian Neuroscience Institute, and the Said Business School, at the University of Oxford.

I have supervised two undergraduate projects, two MSc projects and four PhD students. Currently, I am supervising 6 PhD students in my research group: https://www.darth-group.com/

 

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