I am currently part of a cross-institutional research group in Limerick, based in both TUS and UL. We investigate the use of Machine Learning algorithms in the automatic design of digital circuits on FPGA boards.

I have been taking up teaching hours as a PhD candidate on areas such as Machine Learning and Data Analytics, PLC Programming, Engineering Mathematics, Physics, Electronics and Programming, on both undergraduate and postgraduate levels.

I am currently part of a cross-institutional research group in Limerick, based in both TUS and UL. We investigate the use of Machine Learning algorithms in the automatic design of digital circuits on FPGA boards.

I am responsible for the administration of a departmental computer network and websites: Linux server configuration and management; network equipment maintenance: switches, routers, access points, hubs and cabling; websites development and maintenance: PHP, HTML, CSS, Content Management Systems.

As a Research Assistant my role was to help on the digitalisation journey of SMEs in the mid-west region of Ireland. I have been responsible for the development of training material and delivery of classes in areas such as Artificial Intelligence, Robotics, Automation and Industry 4.0 technologies, as well as supporting RDI projects in collaboration with industry.

I have been collaborating with the InCASE Project in TUS with my engineering expertise since its beginning, back in 2016, as a co-author to its initial feasibility study and original proposal. The project, which has received nearly €1 Million in funding, investigates the use of an intelligent cognitive assistance system on manual-based assembly operations in quality-critical industries, such as medical devices, automotive and electronics. The system relies on computer vision technology and deep… Show more I have been collaborating with the InCASE Project in TUS with my engineering expertise since its beginning, back in 2016, as a co-author to its initial feasibility study and original proposal. The project, which has received nearly €1 Million in funding, investigates the use of an intelligent cognitive assistance system on manual-based assembly operations in quality-critical industries, such as medical devices, automotive and electronics. The system relies on computer vision technology and deep learning to identify and classify assembly steps as compliant or not to instructions, as well as providing an "inputless" immersive instruction delivery system. Show less

Master of Engineering Degree by research on Electrical Engineering, focusing on Industry 4.0 technologies, energy efficiency, machine learning and data analysis. Thesis title: "Development of a Machine Learning Web Application for the Analysis of Energy Data in Production Operations".

Research in Industry 4.0 technologies, development of case studies, brokerage and support to SMEs in accessing funding streams, elaboration of innovation projects and proposals, management and reporting of research projects.

800 hours mandatory internship towards the Electronics Technician degree. I had the opportunity to work with maintenance and management of voice and data IT equipment. PABX configuration and management.