People

Dr Tasos Papastylianou

Postdoctoral Research Fellow (IPHW)
School of Computer Science and Electronic Engineering (CSEE)
Dr Tasos Papastylianou

Profile

Biography

I am a Research Fellow in Health Informatics at the Institute of Public Health and Wellbeing, at the University of Essex. As part of the role I am also acting as a probationary Lecturer for the School of Computer Science and Electronic Engineering. My academic research focuses on clinical and public health applications of Artificial Intelligence and Machine Learning. In particular, I’m interested in: data analysis and information fusion from biological signals (e.g. Brain Computer Interfaces, wearables, hospital-derived, etc) and digitised health data; medical image analysis, explainability, and appropriate validation; AI or tech-oriented public health interventions, and the use and benefits of free and open-source software in medicine. Before this I have worked as a Senior Research Officer at the Brain-Computer Interfaces and Neural Engineering (BCI-NE) lab at the University of Essex, working on a US-UK Bilateral Academic Research Initiative (BARI) project led by Prof. Riccardo Poli, looking at the use of Brain-Computer Interfaces (BCIs) for optimal human-AI collaborative decision-making. Prior to this I worked as a Senior Research Officer in Machine Learning and Biomedical Signal analysis, analysing wearable and smartphone-related data in the context of mental health management and prediction, as part of the EU Nevermind Project, a large European collaboration (led locally by Prof. Luca Citi), involving both academic and commercial collaborators. I was awarded my DPhil in November 2017, in the area of Biomedical Engineering, and specifically Medical Image Analysis, via the CDT in Healthcare Innovation at the University of Oxford. During that time I also co-founded of Sentimoto Ltd, a company with a focus on Wearables for Older Adults, which won several awards in that space (up to £39k in award funding during my involvement). During my time in Oxford, I also took part in an international project which lead to local government policy change -- this involved automated monitoring and maintenance of water pumps in rural Kenya, in collaboration with local start-ups and government. I am also a qualified physician with NHS experience, as well as a concert pianist (I won Young Musician of the Year way back in 1999 in Cyprus), and a keen squash player. I'm always up for a chat over coffee with interesting people (and/or fellow computer nerds!).

Research and professional activities

Research interests

Clinical and public health applications of Artificial Intelligence and Machine Learning

Key words: Machine Learning applied to biomedical signals
Open to supervise

Teaching and supervision

Current teaching responsibilities

  • Advanced Programming (CE303)

Publications

Journal articles (4)

Kampouridis, M., Evdokimov, I. and Papastylianou, T., (2023). Application Of Machine Learning Algorithms to Free Cash Flows Growth Rate Estimation. Procedia Computer Science. 222, 529-538

Carli, V., Petros, NG., Hadlaczky, G., Vitcheva, T., Berchialla, P., Bianchi, S., Carletto, S., Christinaki, E., Citi, L., Dinis, S., Gentili, C., Geraldes, V., Giovinazzo, L., Gonzalez-Martinez, S., Meyer, B., Ostacoli, L., Ottaviano, M., Ouakinin, S., Papastylianou, T., Paradiso, R., Poli, R., Rocha, I., Settanta, C., Scilingo, EP. and Valenza, G., (2022). The NEVERMIND e-health system in the treatment of depressive symptoms among patients with severe somatic conditions: A multicentre, pragmatic randomised controlled trial. eClinicalMedicine. 48, 101423-101423

Qian, G., Toizumi, M., Clifford, S., Le, LT., Papastylianou, T., Satzke, C., Quilty, B., Iwasaki, C., Kitamura, N., Takegata, M., Bui, MX., Nguyen, HAT., Dang, DA., van Hoek, AJ., Yoshida, LM. and Flasche, S., (2022). Association of pneumococcal carriage in infants with the risk of carriage among their contacts in Nha Trang, Vietnam: A nested cross-sectional survey. PLOS Medicine. 19 (5), e1004016-e1004016

Christinaki, E., Papastylianou, T., Carletto, S., Gonzalez-Martinez, S., Ostacoli, L., Ottaviano, M., Poli, R. and Citi, L., (2020). Well-being Forecasting using a Parametric Transfer-Learning method based on the Fisher Divergence and Hamiltonian Monte Carlo. EAI Endorsed Transactions on Bioengineering and Bioinformatics. 1 (1), 166661-166661

Conferences (7)

Habbab, F., Kampouridis, M. and Papastylianou, T., (2023). Improving REITs Time Series Prediction Using ML and Technical Analysis Indicators

Christinaki, E., Papastylianou, T., Poli, R. and Citi, L., (2019). Parametric Transfer Learning based on the Fisher Divergence for Well-being Prediction

Papastylianou, T., Dall’ Armellina, E. and Grau, V., (2016). Orientation-Sensitive Overlap Measures for the Validation of Medical Image Segmentations

Papastylianou, T., Kelly, C., Villard, B., Dall’ Armellina, E. and Grau, V., (2015). Fuzzy Segmentation of the Left Ventricle in Cardiac MRI Using Physiological Constraints

Zhu, T., Behar, J., Papastylianou, T. and Clifford, GD., (2014). CrowdLabel: A crowdsourcing platform for electrophysiology

Zhu, T., Osipov, M., Papastylianou, T., Oster, J., Clifton, DA. and Clifford, GD., (2014). An intelligent cardiac health monitoring and review system

Papastylianou, T., Behar, J., Guazzi, A., Jorge, J., Laranjeira, S., Maraci, MA., Clifford, GD., Hope, RA. and Thomson, P., (2014). Smart handpumps: Technical aspects of a one-year field trial in Rural Kenya

Grants and funding

2023

Yu Life Limited KTP 22_23 R4

Innovate UK (formerly Technology Strategy Board)

Contact

tasos.papastylianou@essex.ac.uk

Location:

CH.G.1 CLINGOE HOUSE, Colchester Campus

Academic support hours:

Tuesdays 10:00-12:00