PhD Program in Computer and Control Engineering
PhD Student: Eliana Pastor
Context of the research activity
The availability of massive datasets currently denoted as “big data” characterizes many application domains (e.g., IoT‐based systems, energy grids). Big Data stresses the limits of existing data mining techniques and sets new horizons for the design of innovative techniques to address data analysis.
The objective of the research activity is the definition of big data analytics approaches to analyze IoT streams for a variety of applications (e.g., sensor data streams from instrumented cars).
The following steps (and milestones) are envisioned.
- Data collection and exploration. The design of a framework to store relevant information in a data lake. Heterogeneous data streams encompassing custom proprietary data and publicly available data will be collected in a common data repository. Tools for explorative analysis will be exploited to characterize data and drive the following analysis tasks.
- Big data algorithms design and development. State-of-the-art tools and novel algorithms designed for the specific data analysis problem will be defined (e.g., to predict component failures).
Knowledge/model interpretation. The understanding of a discovered behavior requires the interaction with domain experts, that will allow operational validation of the proposed approaches.
Skills and competencies for the development of the activity
The candidate should have excellent programming skills, programming experience in the Hadoop/Spark ecosystem, good knowledge of machine learning algorithms.