Rafael Savi

ADAS - Advanced Driver Assistance Systems

Research and implementation of an approach to evaluate reliability of products based on historical repair data. Comparison of traditional methods and machine learning based techniques.

Supported students in practical experiments involving LabVIEW, signal analysis and acquisition (DAQ)

Management and system design of a test bench to test electric controls for offshore winch and crane applications, such as Active Heave Compensation (AHC) using hydraulic actuators; Requirements analysis and documentation of an international project; Design and programming of software for deep-sea electro-hydraulic valve actuators

Software developer in a project aimed to detect flaws in gas distribution pipes by the use of Shearography technique. The daily tasks were software development using C# and WPF including image processing and analysis

Developed a website and server using HTML/CSS and JavaScript

Worked as a researcher at the project SincroBUS, a system developed to control and support in real-time city buses. Daily tasks were to study equipment and sensors for traffic solutions

Master degree focused on reliability analysis of products failures and inference of market share for product repairs. Research fields are failure analysis and machine learning

Studies focused on Solar and Wind Energy

The main study fields are Electrics, Computational Systems, Control and Mechatronics. This includes especially Signal Analysis and Acquisition, System Modelling, Programming in different architectures and languages, Sensor Technologies and Robotics.