MSCA ELITE-S Fellow

Mohammed Al-Rawi

Trinity College Dublin

Al-Rawi is a researcher in the field of computer vision and machine learning and is interested in analysing images as well as other data.

Throughout his career, Rawi has worked in a few academic institutions, e.g., IBILI – University of Coimbra, DETI – University of Aveiro (Portugal); and his latest research position before moving to Dublin was at the Computer Vision Center – Autonomous University of Barcelona (Spain).

Lately, he has been using deep learning to develop and test different AI models; e.g., those related to word-spotting, text embedding, text generation, sentiment analysis, image classification, multitasking, fashion segmentation. etc.

He is very interested in applying AI in the fashion field, focusing on fashion data standardisation, computer vision techniques and natural language processing; and ultimately, fashion recommender systems.

Al-Rawi joined ADAPT as Elite-S research fellow and will be working on his project idea “Digital Data Organisation and Exchange in Fashion (DDOEF; /diːdɔɪf/ )”.

The project aims to develop an ICT Standard supporting the application of artificial intelligence (AI) in fashion and related clothing industries. Through DDOEF, he wants to bridge the gap in data exchange between various fashion manufacturers, retailers and third-party AI companies.

Al-Rawi has a vision that such a standard would facilitate the provision of fashion-related recommendations and many other services to both industry and customers. He is therefore highly enthusiastic about his project and hopes that the standard he is drafting will be accepted by the fashion industry.

Al-Rawi looks forward to continuing working on fashion AI after Elite-S and to make DDOEF a living document and a recognised standard. He, therefore, considers the Elite-S fellowship an important milestone in his career, if not the most important. Al-Rawi’s project will be hosted at the ADAPT Centre, Trinity College Dublin.

Website: https://sites.google.com/view/ddoif