Active Projects

I serve as a Galway lead on the NWCAM2 (North West Centre for Advanced Manufacturing 2), supervising two PhD students and one postdoctoral researcher. NWCAM2 is a €9.98 million cross-border initiative funded through the PEACEPLUS programme and led by Catalyst, in partnership with ATU, North West Regional College, Ulster University, Trinity College Dublin, and Irish Manufacturing Research Centre.

Our work within NWCAM2 focuses on facilitating the deployment of robots in Irish manufacturing SMEs. A central challenge for smaller manufacturers is not only programming and integrating robots into existing workflows, but doing so safely and flexibly, allowing robots to be rapidly reconfigured as production needs change. By combining applied research with direct industry engagement, we aim to develop solutions that make adoption safe, accessible, and adaptable, helping SMEs strengthen their competitiveness while building more sustainable and resilient manufacturing operations. 

The MATX project, part of a broader ATU initiative, TU RISE, to expand its research capacity, involves training 60 PhD researchers across five cohorts. I serve as Co-Lead of the MATX Project alongside Dr Saritha Unnikrishnan and Dr Emmett Kerr. 

The objective of the “MATX – MedAgriTech AI eXcellence” PRTP is to rapidly advance AI expertise and applications across Northern and Western Ireland, via partnerships with regional industry, collaboration with national research institutes, and alliances with international academics.  MATX has brought together over 25 external collaborators; 12 host companies across Northern and Western Ireland; three SFI research centres in artificial intelligence and data science; and one research centre in Agritech. 

I am the Team Lead and Principal Investigator (PI) of the RoboMate project, a National Challenge Fund project supported by Research Ireland (formally SFI). The project aims to develop a software and control architecture that enables non-expert users to efficiently program and re-configure collaborative robots within Irish manufacturing. In doing so, we seek to enhance workers’ capabilities and improve ergonomic outcomes. 

The solution is an accessible and rapidly deployable collaborative robotic system, acting as a smart tool that operators—irrespective of technical background, age, or ability—can program to perform repetitive tasks. It enables untrained workers with task experience to teach and guide the robot during physical operations, effectively positioning the worker as the robot's supervisor. The resulting team would combine the intelligence and experience of human workers with the robot's ability to carry out repetitive tasks accurately, enabling flexible at-volume manufacturing without the reliance on low-cost labour.