Responsible for the design and development of sunroof motors and electronics. HW and SW development of sunroof modules.Responsible for the completion of the project lifecycle according project plans and related milestones, customer requirements and specifications.Direct contact with both customer and supplier offering full engineering support for a successful product realization. Responsible for research and development of analytical models describing the dynamical behavior of sunroof systems using Matlab and Simulink.Organizational skills and capability in setting priorities supporting internal design and validation teams.Students final thesis supervision.

Wireless Energy Transport and Harvesting• Occupation or position held:Intern. –Thesis Project • Main activities and responsibilities:Design and Realization of a Frequency Selective Surface for RF Energy Harvesting and Power Transport Applications.For this thesis work, a methodological approach based on analytical equations in-house developed, is used. The design is validated by using full wave analysis (by means of the software package CST Microwave Studio ), and through the realization of the final structure. Measurements with a Vector Network Analyzer are performed in order to test the analytical model.

Type of business or sector Wireless Energy Transport Main activities and responsibilities Design and realization of a broadband Yagi-Uda rectenna capable of harvesting RF energy from a Digital Video Broadcasting (DVB) transmission station.

Name and address of employer; Type of business or sector Brain Innovation – fMRI Data Analysis, Maastricht, The Netherlands • Occupation or position held; Research and development of new analysis methods for MRI data (for more information please refer to the project website http://mbic.unimaas.nl/);Development of classification and regression algorithms aim to analyse multivariate fMRI data using machine learning and pattern recognition techniques.Efficient implementation of Sparse Bayesian Models and Gaussian Processes using Matlab and C++ programming languages.

Multivariate fMRI data analysis with sparse bayesian models:Efficient implementation of regression and classification algorithms.