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The BioHIT Group of SKEL Lab organises, an open to all, online lecture on Monday 21 September 2020 at 12.00 noon with visiting speaker Dr. Athanasios Tsanas, entitled Harnessing speech signals to develop accurate and robust decision support tools: applications in biomedicine and the life sciences. 


Biomedical speech signal analysis has been gaining increasing momentum in the last 10-15 years. In this talk, I will focus on the key principles and state of the art signal processing algorithms to characterize sustained vowels and voice fillers. My aim is to demonstrate how the extracted characteristics from speech signals can be combined with machine learning techniques to develop robust, automated decision support tools assisting experts on their day-to-day praxis in the context of medical applications and forensic applications. I will highlight contemporary challenges and areas for further development, in particular with large speech databases that we have recently reported on such as the Parkinson’s Voice Initiative where we have collected 18,000+ samples across seven countries.


Speaker Bio

Dr. Athanasios Tsanas, BSc, BEng, MSc, DPhil (Oxon), SMIEEE, FHEA, FRSM
​Thanasis studied Engineering and completed a DPhil (PhD) in Applied Mathematics at the University of Oxford (2012). He 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). He is currently an Associate Professor in Data Science at the Usher Institute, Edinburgh Medical School, University of Edinburgh. He leads the development and delivery of ‘Clinical Decision Support and Actionable Data Analytics’ in the innovative £6m NHS Digital Academy leadership programme. 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), the young scientist award (MAVEBA, 2013), the EPSRC Statistics and Machine Learning award (2015), and won a ‘Best reviewer award’ from the IEEE Journal of Biomedical Health Informatics (2015). 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.

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