Kankoé Lévi Sallah
About Kankoé Lévi Sallah
Kankoé Lévi Sallah is a lecturer in Biostatistics with extensive academic and professional experience in health data analysis. He currently works at AP-HP in Paris and has founded a center focused on public health research in Lomé, West Africa.
Work at Aix-Marseille University
Kankoé Lévi Sallah has served as a Lecturer in Biostatistics at Aix-Marseille Université since 2011. In this role, he contributes to the academic development of students in the field of biostatistics, focusing on statistical methods applicable to health data. His long tenure at the university highlights his commitment to education and research in this discipline.
Current Role at AP-HP
Since 2018, Kankoé Lévi Sallah has been employed as a Health Data Specialist at Assistance Publique - Hôpitaux de Paris (AP-HP). In this position, he applies his expertise in biostatistics to analyze health data, supporting clinical decision-making and research initiatives within the hospital network in the Paris region.
Founder and Coordinator of Research Center
Kankoé Lévi Sallah is the Founder and Coordinator of the Center for Methodology and Modeling - Public Health, Malaria, Infectious Diseases, established in Lomé, West Africa, in 2017. This center focuses on advancing research methodologies and modeling techniques to address public health challenges, particularly in the context of malaria and infectious diseases.
Educational Background
Kankoé Lévi Sallah completed his Ph.D. in Biostatistics and Medical Informatics at Aix-Marseille Université from 2013 to 2017. Prior to this, he studied Spatial Statistics at Lancaster University, where he achieved a GEOSTAT certification in 2015. He also holds a Doctor of Medicine (MD) degree from the University of Lomé and Bordeaux University, which he completed between 1998 and 2007.
Focus Areas and Research Interests
Kankoé Lévi Sallah focuses on the challenges associated with Information Systems, Electronic Health Records, Big Data, Data Sciences, and AI/Machine Learning in health research. He believes in the potential of routinely collected data to generate new knowledge and research hypotheses, emphasizing the importance of data-driven decision-making in healthcare.