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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.
PhD SECO Sustaianbility
Queens University
M.A.Sc Data Science
Polytechnique Montreal
My work bridges theory and practice, addressing fundamental questions on the WHY, HOW, and WHAT of sustainable and trustworthy AI in complex socio-technical ecosystems.
In parallel, I actively contribute to the scientific community as a core reviewer for leading conferences and journals, including ICSE, EMSE, TOSEM, NeurIPS, AAAI, SANER, and MSR. Through these roles, I help uphold scholarly standards and foster innovation in software engineering and artificial intelligence. Additionally, as an international judge for science and engineering competitions, I mentor and support emerging scientists, advancing the next generation of scientific discovery and leadership.
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