Keynote speaker Prof. Athena Vakali

Quantified Self and Sensing Data Analytics

Bio: Athena Vakali [female] is a professor at the School of Informatics, Aristotle University, Greece, where she leads the Laboratory on Data and Web science. ( Datalab ). She holds a PhD degree in Informatics (Aristotle University), a MSc degree in Computer Science (Purdue University, USA), and BSc degree in Mathematics.

Her current research interests include Data Science topics with emphasis on big data and online social networks mining and analytics, human-centric applications and sensing analytics, and on online sources data management on the cloud, the edge and decentralized settings. She has supervised 12 completed PhD theses and she has been awarded for her educational and research work which is extended with mentoring and students empowerment (ACM, ACMW). Prof. Vakali has published over than 190 papers in refereed journals and Conferences and she is Associated Editor in ACM Computing Surveys Journal, in the editorial board of the “Computers & Electrical Engineering” Journal, and ICST Transactions on Social Informatics (her publications received over 9700 citations with hindex=41 according to google scholar). She has coordinated and participated in more than 25 research projects in EU FP7, H2020, international and national projects. She has served as a member in the EU Steering Committee for the Future Internet Assembly (2012-14) and she has been appointed as Director of the Graduate Program in Informatics, Aristotle University (2014-15). She has co-chaired major Conferences Program Committees such as : ACM Gender Equality Summit (Greek Chapter) 2022, PC co-chair at the ACM/IEEE Web Intelligence Conference 2019, the EU Network of Excellence 2nd Internet Science Conference (EINS 2015), 15th Web Information Systems Engineering (WISE 2014), 5th International Conference on Model & Data Engineering (MEDI 2015), etc. She has also served as Workshops co-chair and has been a member to numerous International conferences and Workshops.

Abstract: In recent years, we are witnessing extensive broadening of the Web towards Web of Things, Ubiquitous, and Mobile Computing. The Web of Things is multifaceted, touching upon fields from smart homes and smart cities to retail and digital health. Omnipresent sensored devices continuously track individuals’ activities, and nowadays the “quantified self” i.e. self-knowledge through numbers has become a default option. In this talk, we will unveil the untapped opportunities of the quantified self and sensing data analytics, focusing on a human-centric positive behaviour change technology. Specifically, we will explore the success factors of human-computer interaction in ubiquitous behaviour change technology and the heterogeneous aspects of user engagement in this emerging medium, compared to conventional metrics. We will also discuss the implications of different design choices for diverse user segments and pave the way for the sensing-based services personalization. To illustrate our points, we will present work in the field of personalised and adaptive goal-setting in personal informatics utilising data management processes and mining techniques common across. What have we learned along the way? Where is the future of the sensing data analytics heading