Richard Moulton
President at HAS-Motion
Kingston, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolRichard Moulton is a data-driven software leader and applied research engineer with nine years of experience building analytical tools for biomechanics and neuroscience, now serving as President of HAS-Motion in Kingston, Ontario. He combines a PhD in Electrical and Computer Engineering and an MSc in AI with hands-on C++/Qt development to maintain and evolve core tools like Visual3D and Sift for large motion-capture datasets. Richard’s background in the Canadian Armed Forces—where he established training and operational standards for the nascent Space Operations Centre—underscores his strength in disciplined program development and cross-functional leadership. An active open-source contributor, he implemented the D-Stream clustering algorithm in the widely used MOA stream-mining framework, reflecting deep expertise in streaming ML and anomaly detection. He balances product-focused engineering with ongoing research in data mining and visualization, aiming to put state-of-the-art analytics directly into researchers’ hands.
9 years of coding experience
5 years of employment as a software developer
Bachelor of Science (BSc), Computer Science, Honours, Bachelor of Science (BSc), Computer Science, Honours at Royal Military College of Canada/Collège militaire royal du CanadaDoctor of Philosophy - PhD, Electrical and Computer Engineering, Doctor of Philosophy - PhD, Electrical and Computer Engineering at Queen's UniversityMaster of Computer Science, Artificial Intelligence, Master of Computer Science, Artificial Intelligence at University of Ottawa
English, French
Github Skills (5)
javas10
machine-learning10
machine-learning-algorithms10
clustering10
java10
Programming languages (4)
Github contributions (5)
Waikato/moa
Aug 2017 - Jan 2019
MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:27 commits, 5 PRs, 10 comments in 1 year 6 months
Contributions summary:Richard implemented the D-Stream clustering algorithm within the MOA framework. Their primary contribution involved integrating the D-Stream algorithm, including its core Java implementation. The user's work directly aligns with the project's focus on data stream mining and machine learning algorithms, providing a density-based clustering method. The commit details cite the foundational paper for the D-Stream algorithm, indicating a commitment to accuracy and proper implementation.
pythondata-streamstreamdriftclassification
richard-moulton/moa
Aug 2017 - Jan 2019
MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.
Contributions:16 PRs, 17 pushes, 6 branches in 1 year 6 months
pythondata-streamstreamdriftclassification
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