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☕️Armstrong Foundjem
Chief Scientist
About Me
Dr. Armstrong is a researcher at the intersection of software ecosystem sustainability, affective computing, the trustworthiness of safety-critical systems, and software engineering for machine learning applications, including foundational models, AIWare, and Agentware. He mines massive datasets, including software repositories, and applies socio-technical data science techniques to uncover patterns and empirically make informed decisions.
Interests
- Affective Computing
- Artificial Intelligence
- Data Science
- AI Trusthworhiness AI
- Safety-critical systems
- SECO Sustaianbility
- Carbon foorprint/ Climate change
Education
PhD SECO Sustaianbility
Queens University
M.A.Sc Data Science
Polytechnique Montreal
📚 My Research
Use this area to speak to your mission. I’m a research scientist in the Moonshot team at DeepMind. I blog about machine learning, deep learning, and moonshots.
I apply a range of qualitative and quantitative methods to comprehensively investigate the role of science and technology in the economy.
Please reach out to collaborate 😃
Featured Publications
Recent Publications
(2024).
An empirical study of testing machine learning in the wild.
ACM Transactions on Software Engineering and Methodology.
(2024).
Deep learning model reuse in the huggingface community: Challenges, benefit and trends.
IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
(2023).
A Grounded Theory of Cross-community SECOs: Feedback Diversity vs. Synchronization.
IEEE Transactions on Software Engineering.
(2023).
Studying the Practices of Testing Machine Learning Software in the Wild.
arXiv preprint arXiv:2312.12604.
(2022).
A mixed-methods analysis of micro-collaborative coding practices in OpenStack.
Empirical Software Engineering.
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