Luís Cruz [ Research | Publications | Teaching | Blog ]
My primary research focuses on Green AI and Green Software. I work on establishing techniques, guidelines, and practices to ensure the development of energy-efficient AI systems is straightforward and accessible, without requiring specialized expertise.
You can check some of my publications in this page or in my academic profiles: Google Scholar, dblp, orcid.
List of news articles covering my research.
‘Factura de electricidade para treinar e usar sistemas de IA é uma brutalidade’. 2024
‘A IA não terá emoções. Pelo menos como as conhecemos’. 2024
‘Por cada 30 interações com o ChatGPT, meio litro de água evapora-se’. 2024
‘ENTREVISTA: É preciso “evangelizar” sobre ‘software’ verde como IA’. 2024
‘Pode haver uma Green AI? Investigador português defende que sustentabilidade é obrigatória’. 2024
AI is een oplossing én een probleem voor klimaatverandering?. 2024
Hoeveel water en energie gebruikt uw favoriete chatbot?. 2024
AI-expert Luís Cruz: ‘De efficiëntie van AI wordt afbetaald met grote ecologische voetafdruk’. 2024
Sustainable artificial intelligence: from ChatGPT to green AI. 2023
Kunstmatige intelligentie vreet stroom, één opdracht hetzelfde als een uur een lamp aan.
TV report
and online article.
2023
Zorgen over de negatieve gevolgen van AI voor de mensheid waren er al, maar nu blijkt dat Artificiële Intelligentie ook enorm veel stroom kost. Daarmee is het ook een probleem voor het klimaat. #Nieuwsuur pic.twitter.com/YojIF1tcXv
— Nieuwsuur (@Nieuwsuur) May 31, 2023
EnvironmentalVariables, episode 8, talking about Green Software education. 2022
Green Software Development Is The Only Software Development We Need. 2022
Build environmental sustainability into your development teams 2021
I have/had the privilege of working with wonderful students:
(TU Delft) Engineering Artificial Intelligence in the Wild. Ongoing. Graduating in 2025.
(TU Delft) Concept drift adaption for AIOps. Ongoing. Graduating in 2025.
(TU Delft) Incident Management in Large Fintech Organisations. Ongoing.
(UPC Barcelona Tech) Green AI. Ongoing. Graduating in 2027.
Greening Space Engineering Software. Ongoing.
Lowering Carbon Emissions within AI Models. Ongoing.
Investigating energy hotspots with Docker and Tracing. Ongoing.
Energy testing in Mobile Software. June 2024
E-Compare: Energy Regression Testing for Software Applications. June 2024
Approximated Computing in Continuous Integration Pipelines. May 2024
Sustainability of Edge AI at scale. May 2024
Measuring up to stability: Guidelines towards accurate energy consumption measurement results of Rust benchmarks. With Simula Research Lab. May 2024
Catalog of Energy Patterns for Websites. April, 2024
Green Quantization. April 2024
Minimize experimentation overhead through dataset selection, approximated pipeline execution using proxy models, and data collection feedback. May 2024
GreenAI for Deep Learning Ensembles. With Deloitte. April 2024
(TU Delft) Hawkes processes for large scale service systems. With AI4Fintech – ING September 2023
(TU Delft) EasyCompress – Automated Compression for Deep Learning Models, July 2023.
(TU Delft) EDATA: Energy Debugging And Testing for Android, June 2023.
(TU Delft) How to remove dependencies from large software projects with confidence. With ING. August 2022.
(TU Delft) Building a generalisable ML pipeline at ING, July 2022.
(TU Delft) Automated Detection of Code Smells for Machine Learning Applications, July 2022.
(TU Delft) Detecting anti-patterns in a MSA using distributed tracing, July 2022.
(TU Delft) Detecting PII in Git commits, July 2022.
(TU Delft) Green AI, July 2022.
(TU Delft) A Human-In-the-Loop System for Interpreting Image Recognition Models, June 2022.
(TU Delft) Engineering Best Practices for Machine Learning projects, October 2021.
(TU Delft) AI Model Lifecycle Management: Systematic Mapping Study and Solution for AI Democratisation, November 2020.
(IST) Automatic refactoring for energy efficiency in continuous integration pipelines, September 2020.
(TU Delft) Studying the Machine Learning Lifecycle and Improving Code Quality of Machine Learning Applications, July 2020.
(IST) Detecting User Sessions and Inferring User Satisfaction in the Context of a Search Engine for Legislative Contents, December 2019.
CAIN, 2023.
MOBILESoft, 2023.
MSR, 2023.
MAP-i Doctoral Programme in Computer Science, University of Porto 2019.
BENEVOL, The 18th Belgium-Netherlands Software Evolution Workshop, 2019.
CIbSE XXI Ibero-American Conference on Software Engineering, 2018.
Faculdade de Engenharia da Universidade do Porto, 2008.