Jean-Didier Totow Tom-Ata
Papers
1
Total Citations
2
H-Index
1
About
Jean-Didier Totow Tom-Ata is a researcher focused at the intersection of data-driven infrastructure management and artificial intelligence for IT operations (AIOps). His work addresses the growing complexity of managing distributed, containerized applications on heterogeneous cloud and cluster environments, particularly for big data workloads. His most-cited paper, "Leveraging Data-Driven Infrastructure Management to Facilitate AIOps for Big Data Applications and Operations" (2021), proposes novel frameworks that use data analytics to automate and optimize infrastructure decisions, reducing operational costs and improving system reliability. While his citation count is currently modest, his research tackles a critical challenge in modern computing: the scalability and efficiency of data-intensive systems. Totow Tom-Ata’s contributions are particularly relevant as organizations increasingly adopt hybrid cloud architectures and seek intelligent, automated solutions for performance monitoring and resource allocation. His work lays foundational groundwork for integrating AI-driven insights into operational workflows, promising to enhance both the resilience and cost-effectiveness of big data platforms.
Research Focus
Key Achievements
Top Papers
- 1