M.Sc. Agustin Zuñiga Corrales defends his doctoral thesis "Pervasive Data Science: From Data Collection to End-User Applications" on Thursday the 2nd of November 2023 at 12 o'clock in the University of Helsinki Main building, hall Karolina Eskelin (U3032, Fabianinkatu 33, 3rd floor). His opponent is Professor George Roussos (Birkbeck College, University of London, UK) and custos Professor Petteri Nurmi (University of Helsinki). The defence will be held in English.
The thesis of Agustin Zuñiga Corrales is a part of research done in the Department of Computer Science and in the Pervasive Data Science group at the University of Helsinki. His supervisors have been Professor Petteri Nurmi (University of Helsinki), Professor Pan Hui (University of Helsinki and HKUST, Hong Kong) and Associate Professor Huber Flores (University of Tartu, Estonia).
Pervasive Data Science: From Data Collection to End-User Applications
Pervasive Data Science (PDS) is an emerging paradigm that combines the Internet of Things, Pervasive Computing, and Data Science to address everyday challenges. PDS differs from traditional data science in that it harnesses data from pervasive computing deployments, which affects the way data is produced and how it can be analyzed. To date, PDS has received limited attention as an independent research domain as the research field is fragmented and scattered among many different subfields. This is due to a limited understanding of the characteristics and challenges in PDS, and a lack of end-user applications that demonstrate the benefits of PDS. This thesis paves the way for improving the adoption of PDS by offering (i) insights into the processes that produce data, (ii) demonstrating how pervasive computing deployments can enable wide-range of applications by re-purposing existing sensors and capabilities of pervasive computing devices, and (iii) highlighting the potential benefits of Pervasive Data Science by developing end-user applications for tackling sustainable development.
Availability of the dissertation
An electronic version of the doctoral dissertation will be available on the e-thesis site of the University of Helsinki at http://urn.fi/URN:ISBN:978-951-51-9973-7.
Printed copies will be available on request from Agustin Zuñiga Corrales: email@example.com.