Energy Cost and Machine Learning Accuracy Impact of k-Anonymisation and Synthetic Data Techniques. - Pepijn de Reus; Ana Oprescu; Koen van Elsen (ICT4S, 2023)

Exploring the Impact of K-Anonymisation on the Energy Efficiency of Machine Learning Algorithms. - Vit Zemanek; Yixin Hu; Pepijn de Reus; Ana Oprescu; Ivano Malavolta (ICT4S, 2024)

An interdisciplinary exploration of trade-offs between energy, privacy and accuracy aspects of data. - Pepijn de Reus; Kyra Dresen; Ana Oprescu; Kristina Irion; Ans Kolk (CoRR, 2024)

Generating Energy-efficient code with LLMs. - Tom Cappendijk; Pepijn de Reus; Ana Oprescu (CoRR, 2024)

An exploration of the effect of quantisation on energy consumption and inference time of StarCoder2. - Pepijn de Reus; Ana Oprescu; Jelle Zuidema (CoRR, 2024)

An exploration of prompting LLMs to generate energy-efficient code. - Tom Cappendijk; Pepijn de Reus; Ana Oprescu (GREENS@ICSE, 2025)