Tassos Koidis long time research interest has been olive oil, its composition and bioactive properties and its authenticity, especially the methods to detect olive oil adulteration. Tassos also worked on cold pressed rapeseed oil produced locally in Northern Ireland resolving its chemical and physical profile, investigating novel pre-processing extraction methods and developing instrumental methods to detect substitution fraud with lesser oils. He had published extensively on this subject and is recognised as an authority within the UK and beyond in the chemistry and authenticity of vegetables oils.

His research has expanded in novel preservation technologies (such as cold plasma, high pressure processing, ultrasound) and their impact on food quality and safety. More recently, his main focus is on developing robust and rapid analytical platforms using vibrational spectroscopy (MID, NIR, Raman) and chemometics to predict the chemical parameters of plant-based foods, including their composition and origin. Using this platform he developed methods for vegetable oils, including palm oil and its derivatives, and coffee (traceability and authenticity) among others. 

Current work includes online NIR sensing to control the black tea processing in pilot scale, a very promising concept for continuous measurements in the production line of food factories that together with a robust e-decision system also in development, would enable managers to take informed decisions in real-time and optimise production.   Last but not least, in collaboration with machine learning experts, he developed a novel multivariate dimensionality reduction method (CLPP) and a comprehensive framework for augmenting spectral data that would help spectroscopy based chemometric models become more universal and independent of the instrument used doing their calibration or testing.