Zeyad Kelani

Assistant Professor of Political Science, Cairo University

Dr. Zeyad Kelani is an Assistant Professor of Political Science at Cairo University. He is a specialist in big data analytics and artificial intelligence, with a particular focus on financial and banking modeling. His academic journey began with a PhD in Computational Analytics from Claremont Graduate University in the United States (2021), which marked the starting point of his commitment to developing data-driven solutions. Dr. Kelani holds a strong academic foundation, including a master’s degree in Applied Data Science from the United States, as well as a dual master’s in Comparative Politics and Society from the American University in Cairo and the University of Tübingen in Germany. He has an extensive record of peer-reviewed journal articles, book chapters, and academic papers addressing advanced data analytics, machine learning, and predictive modeling in social and financial contexts. His expertise notably extends to the innovative use of audience data, GPS data, and geospatial information to enable precise measurement and effective targeting. In addition to his academic and research achievements, Dr. Zeyad Kelani brings practical experience in corporate governance and the financial and banking sector. He has worked at the Central Bank of Egypt on monetary policy issues, giving him deep knowledge of financial policy and economic planning. He has also worked with multilateral development banks, focusing on lending analytics—further strengthening his expertise in designing and evaluating financial strategies aimed at economic development and financial stability. Before his work in the banking sector, Dr. Zeyad Kelani served as a postdoctoral researcher at the Donald Bren School of Information and Computer Sciences at the University of California, Irvine. During this period, he led the data science team at the UC Institute for Prediction Technology, where he played a pivotal role in developing AI and big-data solutions for social and financial modeling, contributing to research projects funded by the U.S. National Institutes of Health (NIH).