Dr. Mohamed Eltabakh’s research expertise falls under the broad areas of big data management, scalable data analytics, distributed data mining and machine learning, and database systems. His research is driven by the fact that the lifecycle of the data, in almost all applications, has never been more complex involving numerous interconnected stages. Dr. Mohamed Eltabakh’s research addresses core challenges in several of these stages including modeling, storing, indexing, querying, and applying analytics--certainly, all with scalability and efficiency in mind. In a nutshell, the combination of the unprecedented scale of the data, the complexity of the data types, and the need for applying advanced workloads and operations drive most of my research. His key areas of research cover AI-driven data management, big data management, database systems, data science, scalable data analytics, distributed data mining and machine learning, time series infrastructures, query processing, and optimization.