Sarini Jayasinghe obtained a bachelor’s degree in Manufacturing Engineering from Peradeniya University in 2016. After completing her bachelor’s degree, she joined the department of Manufacturing Engineering as an assistant lecturer in November 2016 and worked till 2017.

In January 2018, Sarini Jayasinghe started her PhD studies at University of Liverpool (UoL). During her time as a PhD student, she was able to develop a machine-learnt model to identify addditively manufactured build anomalies in real-time. Her main research interests encompasses the fields of manufacturing, control systems and machine learning.

While writing her PhD thesis in Feb 2021 she started working as a part-time research assistant to develop a machine-learnt online model to predict furnace fault density in float glass sheets which will help implement a digital twin for the float glass production. After completing her PhD studies, she continued working full time on the same project as a post-doctoral research assistant. The main topics of her post-doctoral work include implementing a data pipeline to pre-process sensor data collected via process monitoring sensors (i.e., signal processing, signal combination), forecasting future fault density using product of experts Gaussian process regression and model optimization.