Research Topics

Our research focuses on the design, deployment, and runtime management of distributed applications across the cloud-edge continuum.

Model Deployment & Inference in the Cloud-Edge Continuum

Efficient deployment and serving of machine learning models over heterogeneous infrastructure, from cloud data centers to resource-constrained edge nodes.

Self-Adaptive Runtime Management

Autonomic techniques that let distributed applications, such as microservices and data stream processing systems, adapt at runtime to changing workloads and resources.

Serverless Computing in the Cloud-Edge Continuum

Function-as-a-Service platforms and policies that bring the serverless model beyond the cloud, as in our Serverledge framework.

Performance Modeling & Evaluation

Analytical, simulation-based, and experimental methods to predict and assess the performance of distributed systems and guide their design and management.

Cloud-HPC Convergence

Bringing together cloud and high-performance computing to run scientific and data-intensive workloads with the flexibility of the cloud and the efficiency of HPC.