Dirar Sweidan

Dirar Sweidan

Project Description

Whenever data exist, we, as data scientists and researchers, have opportunities to find new ways of exploring and gathering new knowledge from it. For example, when we talk about Bigdata, we usually would mention what is related to e-commerce and what issues can be solved. In this context, the topics of research in this PhD project undertake several aspects that nowadays are highly demanded in retailing, such as how to accurately generating personalized recommendations? How to conduct a meaningful product return analysis for retailers? And so forth.

Generally, and with what is happening around in commerce caused by the coronavirus, the project serves for growth, as well as for survival, in different ways. In other words, we believe that employing artificial intelligence and machine learning in this domain is capable to find new solutions that make a difference in production, increasing sales, improving end-user loyalty, by researching for producing improved or new algorithms and techniques applied in retailing. Such a project is not just to be only an illustration of technical prowess, but also demonstrates academic qualities, and contributes to knowledge someway.

Links:
ORCID
Google Scholar

Thesis Project Team

Dirar Sweidan

PhD Student

Master of Science with a major in Computer Science and Engineering. Specialisation: Embedded and Intelligent Systems.

Ulf Johansson

Supervisor

Jönköping University
& University of Borås

Anders Gidenstam

Co-Supervisor

University of Borås

Joeri van Laere

Co-Supervisor

University of Skövde