Ioannis is a Senior Data Scientist at the ONS Data Science Campus. His research interests are in pattern recognition, machine learning, deep neural networks, image and video processing and human-computer interaction.
He obtained his MEng degree in Civil Engineering from National Technical University of Athens in 2007 and his MSc in Computer Science from University of Bristol in 2009, specialising in visual biometrics. Between 2009 and 2013 he worked in the area of automatic recognition of complex human behaviour in video with computer vision and machine learning for a PhD award at Cardiff University. Before joining the Data Science Campus, Ioannis was a post-doctoral researcher at Cardiff University, working on data science projects related to surveillance and anomaly detection in video in collaboration with the Defence Science and Technology Laboratory (DSTL). His work has been presented in several prestigious international journals and conferences, such as Pattern recognition, International Conference on Acoustics, Speech, and Signal Processing (ICASSP) and International Conference in Computer Vision (ICCV).
We have been working with the Department for Business and Trade (DBT) to show how data science techniques can enable and enhance the analysis of global supply chains.
Read more on Using Natural Language Processing for the analysis of global supply chains
We go behind our analysis on the use of microdata for the examination of preference tariff utilisation and take a deep dive into challenges of drawing together new administrative data sources to answer relevant policy questions.
Read more on The use of microdata for firm-level analysis of preference tariff utilisation in the UK: technical report
Preference utilisation rates (PURs) measure the extent to which UK businesses make use of the zero or reduced tariffs available via free trade agreements (FTAs). In this work, we study the take-up of preferential tariffs by UK businesses between 2009 and 2019 and examine their trends and patterns.
Read more on Employing data science to analyse the use of preferential tariffs in free trade agreements
Synthetic data mimics essential characteristics from the original dataset, creating new, substitute data that does not represent any real person, removing confidentiality requirements.
Read more on Synthetic data for public good and art