About

I am the Lead Machine Learning Engineer at Util. I build end-to-end machine learning pipelines and use large language models to measure the social and environmental impact of publicly traded companies. I also work on MLOps, developing the infrastructure to scale Util’s machine learning models to hundreds of millions of documents. I am responsible for Util’s ML Roadmap and I manage a small team of engineers.

In parallel, I am Nesta’s Generative AI Resident, exploring how large language models can be used for social good. I am focusing on early years education in the UK, building prototypes that advance children’s learning.

Before Util, I was an Open Science Fellow at Mozilla where I worked on interactive information retrieval. I developed a knowledge discovery platform for academic publications that combined a neural search engine with data visualisation. Before Mozilla, I was a Senior Data Scientist at Nesta, the UK’s Innovation Foundation, where I worked at the intersection of machine learning, economics and policy. During my time there, I delivered high-impact projects and consulted the OECD, World Bank, the EU Commission and several national governments. In past, I worked as a Data Scientist at the Digital Catapult where I focused on large-scale web scraping and information extraction. Occasionally, I run Machine Learning workshops while I have advised DataKind on NLP projects.

Born in Athens, Greece, I hold a BSc in Economics, an MSc in Data Science and a black belt in Kung Fu.

I am passionate about open science, data engineering, machine learning and large language models. Get in touch if you would like to chat!