I am a lecturer in AI for speech analysis for health at the Department of Biostatistics and Health Informatics at King’s College London. My current research interests include speech processing, affective computing and multisensory signal analysis. I am fascinated by the application of machine learning techniques to improve our understanding of different health conditions. I am particularly interested in applying these techniques to mental health disorders. I am actively involved in the RADAR-CNS project in which I assists in the management of Work Package 8: Data Analysis & Biosignatures.
I was awarded my PhD in Electrical Engineering from UNSW Australia in February 2016 for my thesis ‘Automatic assessment of depression from speech: paralinguistic analysis, modelling and machine learning’. I was a postdoctoral researcher at the Chair of Complex and Intelligent Systems at the University of Passau, Germany. Most recently, I was a habilitation candidate at the Chair of Embedded Intelligence for Health Care and Wellbeing at the University of Augsburg, also in Germany.
During my time in Germany I was involved in the DE-ENIGMA, TAPAS, sustAGE and RADAR-CNS Horizon 2020 projects, in which my roles include contributions towards management of the technical work packages. I enjoy working towards solving real-world problems in health and wellbeing as part of these inter-disciplinary teams. I also wrote and delivered courses in Speech Pathology, Deep Learning and Intelligent Signal Analysis in Medicine.
I am also an external advisor on the National Science Foundation of China (NSFC) funded project, “Diagnosis of Depression by Speech Signals” (grant No.31860285), led by Dr. Xiaoyong Lu, Northwest Normal University Lanzhou, China.
I have (co-)authored over 100 conference and journal papers leading to over 1900 citations (h-index: 23). I am a frequent reviewer for IEEE, ACM and ISCA journals and conferences as well as serving on program and organisational committees. I am also a member of ACM, ISCA, IEEE and the IET.
Contact me at email@example.com