Sophia Antipolis, France
I am a PhD researcher at the Université Côte d'Azur and the i3s lab - SPARKS team, supervised by Pr. Célia da Costa Pereira.
My research interests are Information Retrieval, Search as Learning and user cognitive modeling. I acquired my Computer Science education at the Lebanese University in Beirut, Lebanon. My previous experience in the industry includes software quality assurance, software developement and project management. I have a passion in knowldge transfer and working with youth.
Participation in the Doctoral Consortium
April 2022, Stavanger, Norway
My participation in the Doctoral Consortium at the 44th European Conference on Information Retrieval provided me a unique opportunity to discuss my overall research project with experts in the Information Retrieval field.
Research Visit to Joint Research Center
May 2022, Ispra, Italy
I had the pleasure to be invited by the European Commission for a research visit to the Joint Research Center in Ispra, Italy. My visit will include some lectures about JRC and some other interesting research topics. The mission will also include some visits to JRC main labs and exchanges with scientific experts.
Making search systems "aware" of the users knowledge
May 2022, Online
Abstract: Current search systems are optimized for simple search tasks, quick results, and sometimes for the user’s interests. They use advanced technologies to retrieve information from large libraries, called indexes. However, they are not designed to support the user’s learning outcome or knowledge change, although they are used every day for many complex learning tasks. Dima will first introduce the topic of Search as Learning, then discuss some research techniques to measure the user’s knowledge and adapt search systems accordingly.
30th ACM Conference on User Modeling, Adaptation and Personalization
July 2022, Barcelona, Spain
Presenting my latest research paper entitiled "User's Knowledge and Search Goals in Information Retrieval Evaluation". The contribution proposes a novel information retrieval evaluation measure that takes into consideration the user's previous knowledge and his/her information needs.