Research Interests

My research focuses on performance evaluation, cloud computing, cyber-physical systems, and uncertainty propagation.

Performance and Dependability Analysis

Performance and dependability analysis of large-scale and complex systems using data analysis, stochastic formalisms (queuing networks, Petri nets, and Markov chains), simulation (discrete-event and agent-based), machine learning, and experimental evaluation. I applied these techniques to a variety of domains, such as, Big Data applications, cloud computing systems, cyber-physical systems, and storage devices.

Cloud Computing

Profiling and modeling of virtual resources for predicting and optimizing the performance of burstable instances and serverless computing in public cloud environments (AWS). Analysis of microservice design patterns for performance enhancement. Developed models account for bursty and heterogeneous workloads, and allow meeting service-level-objectives defined on the latency distribution.

Cyber-Physical Systems (CPS)

The development of CPS applications in critical scenarios requires an accurate model-based design to early predict CPS behavior and mitigate failures that may reduce CPS effectiveness. My research activity focuses on developing model-based techniques for modeling and analyzing large-scale and spatially distributed CPS subject to uncertainty.

Uncertainty Propagation

Analysis of dependability and performance models to investigate how uncertainty on input parameters propagates through a model and affects its output measures.