Who I am

I am a Belfast-based data scientist. I have a PhD in groundwater hydrology from Queen’s University Belfast and a solid background in deep learning, computer vision, NLP and time-series prediction.

During my time in QUB I worked on the formulation of novel image analysis techniques and the application of computer vision algorithms on experimental photographs of saltwater intrusion. The goal of the investigation was the automatic detection of groundwater flow patterns inside synthetic aquifers. This was achieved by conducting classification and regression analysis on the available laboratory data, through testing the implementation of multiple machine learning models. Part of this work has been published in both conferences and scientific journals since 2020. Supplementary to that, I have worked on the application of recurrent neural networks (RNN) for times-series prediction.

I am proficient in three programming languages, and have a deep knowledge of statistics and optimization algorithms. All through my research career, I have had significant involvement in the acquisition and filtering of experimental data. I rarely relied on already processed datasets, obtained from online repositories, for my machine learning models. Instead, the majority of my ML investigations were based on data obtained through our own data acquisition. This gave me valuable insight on the necessary data-engineering skills a successful ML engineer should possess. I am proficient in three programming languages while being familiar with Git, which I use to collaborate with my colleagues on a daily basis, as well as to document my side projects. Last but not least I have a deep knowledge of statistics and nature-inspired optimization algorithms in particular, and I am especially interested in their application in combination with machine learning models.

Take a look in my CV, my published work and my full GitHub profile!