Shaima Algabli

Data Scientist

Shaima is a researcher and data scientist from Yemen who specializes in graph matching, applied machine learning, and deep learning applications. She holds a PhD in Computer Engineering and Mathematics from Universitat Rovira I Virgili, Spain, focusing on embedding node-to-node mappings to learn the graph edit distance parameters. While there, she co-authored peer-reviewed articles in top-tier AI conferences, such as Pattern Recognition, CAIP, and ICPR. In addition, she completed a research internship in Cairo University, Egypt.

Prior to her PhD, she worked in the Yemen branch of the oil corporation Total as a method logistic engineer, building models to organize onsite inventories for supply chain management. There, she also acted as a woman union representative. In addition, she underwent a study program organized by Total’s headquarters. For this program, she spent a year in UAE, Turkey, and Yemen, taking courses in supply chain management, contract engineering, and warehouse inventory.

Shaima also has an MSc in Information Systems Science, as well as BSc in Information Technology Science, from Cairo University, Egypt. For both programs, she was fully sponsored by the Yemen government. As part of her master’s, she worked as a researcher with the remote sensing department of Yemen’s oil and minerals ministry, focusing on detecting changes in the country’s coastal areas. An active volunteer, she also acted as a communication and education manager for six years with One Hand, a non-profit in Yemen that aims to empower local youths through education.