(Short Term Contract)Framework to recognize possible leak via automated content classification.

Complete design and development of ACQUA, a software solution to predict the Quality of Experience of popular applications using machine learning. - Machine Learning: prediction models using supervised learning & active learning - Frontend: Java + Android application; web portal - Backend: NodeJS + Java measurement backend; Python + MongoDB web server - Deployment: VMs, Docker and custom bash scripts - Networking: lightweight measurement system to estimate end to end network conditions Security: privacy & ethical risks assessement - Testing: unit tests; load tests; controlled experimentation - Data Visualization & Analytics: cartography; insights on collected dataThis position is the follow up of my Master Thesis. It is focused on the application of machine learning techniques into a mobile application that performs network measurements.For more information: https://project.inria.fr/acqua/

Machine Learning study to relate network-level measurement to expected Quality of Experience for video streaming applications.Development of a platform to automate controlled experiments and build Quality of Experience models in the network domain.Use of Active Learning (Semi-Supervised Learning) and Machine Learning techniques to build and evaluate the models.

Development and business logic refactoring of internal sofware for the department administraton. Network administration.

Development of a service oriented OWL ontology of the WWTP domain for MAS infrastructures.

Sviluppo driver e architettura di controllo per impianti di depurazione basato su tecnologia Java inambiente distribuito

Complete technical development of Dynamic Fractals, an interactive art installation, where people can manipulate fractals using a motion sensing device (Kinect).