Sustainable Human Like Adaptation: Auto Adaptive Machine Learning for Evolving Real World Systems

About the Project

OPEN FOR UK AND REPUBLIC OF IRELAND STUDENTS ONLY

SPEAR Research Programme: Fully Funded PhD Opportunities

The Semiconductor and Photonics Education and Research (SPEAR) Centre, funded by PEACEPLUS and managed by the Special EU Programmes Body (SEUPB), is a cross-border project that will provide Ulster University and ATU with access to an all-island network of research groups and industry partners. The project receives strategic support from Tyndall and advisory support from Seagate Technology.

This PhD project focuses on developing the next generation of sustainable, self adapting machine learning (ML) systems capable of operating reliably in real world environments that change continuously over time. Building on previous work using Exponentially Weighted Moving Average (EWMA) for covariate shift detection, this PhD will develop an advanced auto adaptive ML framework integrating change point detection (CPD) with modern continual learning strategies. A key feature is the development of real time digital twins. The framework will be applied in brain–computer interfaces (BCIs) and predictive maintenance in smart manufacturing, particularly in photonic device fabrication.