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Mini Track Chair:
Data Science provides insight and understanding of large amount of unstructured and heterogeneous digital sources. Today’s business activities in the modern digital society produces masses of information that needs to be filtered, analysed and structured for prediction and modelling. Text mining, herding analysis and sentiment extraction are quantitative tools to augment forecasts in finance, banking and behavioral economics. Smart data analytics is the way to apply data science in a digital society.
In this track we aim at practitioners and academics that want to present tools and concepts of data science with a strong focus on applications and implementations.
We encourage submission of papers that address emerging needs and the impact of data science on the new digital society.
FinTech aims to improve the efficiency of financial systems using technology. FinTech bring several opportunities (competitive prices, better user experience, wider inclusion) but also risks (credit risks, market risks, cyber risks), amplified by the interconnectedness of FinTech platforms, which generates systemic risks.
We encourage submission of papers dealing with the following subject fields (but not limited to): Digital Banking, Internet Finance, Financial Inclusion, Asset Allocation, Impact Investment, Crypto Currency, Alternative Asset Management, Blockchain Technology, Robo Advising, Text Mining, P2P Financing, Financial Privacy Issues.

is Associate Professor at the Faculty of Business Administration in Foreign Languages (FABIZ), Bucharest University of Economic Studies (ASE), researcher, econometrician and high frequency data specialist, with publications in leading academic journals. His experience covers a broad range of fields, from investments gained as Senior Quantitative Analyst (Asset Allocation) in the Investments Department of a superannuation fund (Mine Super) in Australia to central banking, gained as Principal Economist in the Systemic Risk Monitoring Division, Financial Stability Department of the National Bank of Romania. He also worked as Senior Economist at UniCredit Bank (Romania) and also as Senior Economist in the Government of New South Wales (Australia).

Sadok BEN YAHIA
is a Professor at the Technology University of Tallinn (TalTech) since January 2019. He obtained his Habilitation to Lead research in Computer Sciences from the University of Montpellier (France) in April 2009.
His research interests mainly focus on data-driven approaches for near-real time Big Data analytics, e.g., urban mobility in smart cities (e.g., information aggregation & dissemination, traffic congestion prediction). Fake content fighting, cybersecurity.
For the supervision activities, He supervised 33 PhD Computer Science Students and over 60 master students. A selected list of his publications is shown at a glance through my DBLP web site: http://dblp.uni-trier.de/pers/hd/y/Yahia:Sadok_Ben. In addition, the impact of his publications within the community is shown through the google scholar: https://scholar.google.com/citations?user=uJwhmiUAAAAJ&hl=fr.
He is currently a member of the steering committee of the International Conference on Concept Lattices and their Applications (CLA) as well as the International French Spoken Conference on Knowledge Extractions and Management. Contact him at sadok.ben@taltech.ee.