Rory Mcgrath
Artificial Intelligence Researcher at Accenture AI
Dublin, Dublin 1, Ireland
Summary
🤩
Rockstar🎓
Top SchoolRory Mcgrath is an Artificial Intelligence Researcher with 13 years of experience applying machine learning, knowledge graphs, and explainable AI to industry problems from Dublin. He holds a BEng with first-class honours and an MSc in AI and Robotics, and his PhD work at UC Berkeley produced a generative model of spatially-embedded social networks that integrates real-time spatio-temporal streams with agent-based pedestrian dynamics. At Accenture AI he bridges academic research and production code—developing TensorFlow-based models, investigating deep reinforcement and Bayesian networks, and translating novel papers into industry use cases. His earlier academic work demonstrated practical location-prediction using SVM variants and revealed city “habitats” from location-based social data, showing a strong track record in human mobility inference. An active contributor to open-source ML tooling, he improved efficiency in the known AmpliGraph knowledge-graph embedding evaluation pipeline, reflecting both research depth and pragmatic performance optimization. Colleagues value him for combining rigorous academic methods with production-focused engineering to deliver interpretable, scalable AI solutions.
13 years of coding experience
7 years of employment as a software developer
Master of Science (MSc), Artificial Intelligence and Autonomous Robotics, Master of Science (MSc), Artificial Intelligence and Autonomous Robotics at The University of EdinburghBachelor of Engineering (BEng), Electronic and Computer Engineering, 1 st Class Honours, Bachelor of Engineering (BEng), Electronic and Computer Engineering, 1 st Class Honours at National University of Ireland, Galway
Github Skills (5)
representation-learning10
machine-learning10
knowledge-graph10
tensorflow10
python10
Programming languages (1)
Github contributions (5)
Accenture/AmpliGraph
Jan 2019 - Aug 2019
Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:68 commits, 8 PRs, 22 pushes in 6 months
Contributions summary:Rory primarily focused on improving the efficiency of the knowledge graph embedding model's corruption generation process. They updated the corruption generation logic within the evaluation protocol, optimizing performance. Additionally, they modified the model code to use these new corruption generation references. They also added a script to run single experiments.
python-libraryrepresentationpythonknowledgerepresentation-learning
rorymcgrath/Banana_Collector
Jan 2019 - Mar 2019
Contributions:25 pushes in 1 month
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