Conor Muldoon is an evaluator and seasoned research scientist with 11 years of experience at the intersection of distributed AI, sensor networks, and applied machine learning. He has led university research and lectured advanced modules in software design and algorithms while building production tools for environmental monitoring using Java, Spring Boot, React, PostgreSQL, Docker and Python ML stacks. Conor’s work spans end-to-end systems—from mobile and IoT middleware to explainable ML models (SHAP) for water-quality prediction—and he has translated prototypes into deployed services and apps, including a consumer pivot (Nomsome) that leverages React Native and GPT-3. He represents Ireland on an international COST management committee, reflecting a track record of collaborative, cross-border research. Based in Manchester with a PhD from University College Dublin, he combines academic rigor with practical engineering and a demonstrated ability to move research into operational tools for environmental and infrastructure domains.
11 years of coding experience
9 years of employment as a software developer
B. Sc. (Houours) Computer and Software Engineering, B. Sc. (Houours) Computer and Software Engineering at Technological University of the Shannon, Athlone Campus
Ph.D. Computer Science, Ph.D. Computer Science at University College Dublin
Unison enables the tracking and graphing of (HARMONIE-AROME) numerical weather forecast data from meteorological services and provides an API for accessing historical data.
Contributions:16 releases, 41 PRs, 529 pushes in 5 years 7 months
meteorologyapiweather-forecastnoaatracking
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