About Us#
Our approach combines research insights with practical development efforts, ensuring our project maintains academic rigor while also being applicable in real-world scenarios.
For inquiries related to the project, we encourage you to join the Discord, where you can engage directly with our team. For other matters, you may contact the project leader (Heitor) via Email or Discord.
Core Maintainers#
Active developers who oversee discussions, manage releases, ensure module integration, and handle coding tasks in general. A full list of committers can be found on the CapyMOA GitHub.
Heitor Murilo Gomes is currently a senior lecturer at Victoria University of Wellington (VuW) in New Zealand. Previously, he served as co-director of the AI Institute at the University of Waikato (UoW), where he supervised PhD students and research assistants. From 2020 to 2022, he taught the “Data Stream Mining” course at UoW. His primary research focuses on applying machine learning to data streams, encompassing tasks such as ensemble learning, semi-supervised learning, drift detection and recovery, and the intersection of online continual learning with data streams. Heitor has also made significant contributions to several open-source projects specializing in online and stream learning, notably MOA (Massive Online Analysis), for over a decade.
Anton Lee is a PhD student in AI and a research assistant at the University of Wellington, where they study continual learning. As a research assistant, they maintain the CapyMOA open-source data-stream learning project.
Jia (Justin) Liu is currently pursuing a Ph.D. in Artificial Intelligence at The University of Waikato, focusing on anomaly detection in streaming data. His research addresses the challenges of detecting unusual patterns in dynamic and evolving data streams. Jia’s work explores innovative algorithms and techniques to improve the accuracy and efficiency of real-time anomaly detection, adapting to concept drift and evolving data distributions.
Guilherme is a postdoc at the AI Institute from the University of Waikato. His research interests revolve around Machine Learning for Data Streams, including change detection, anomaly detection, and the development of efficient algorithms.
Yibin (Spencer) Sun is a fourth-year Ph.D. student at the University of Waikato, New Zealand, focusing on advanced machine learning algorithms for streaming data. Yibin is also a contributor to CapyMOA platform, hoping to enrich the community and society of data stream learning and research field.
Nuwan Gunasekara research interests include stream learning, online continual learning, and online streaming continual learning.
Vitor is a machine learning researcher focusing on learning from time-dependent data. He currently holds a postdoctoral research position in the University of Porto, Portugal.
I am a research scientist and PhD student in the field of machine learning and data mining at Karlsruhe Institute of Technology. I focus on learning from sequential data, specifically the intersection between data stream mining and decision making under uncertainty. I am interested in everything that concerns data streams and online learning and I have mainly worked on change detection, incremental decision trees and multi-armed bandits.
Research Advisors#
Experts in their respective fields, these individuals provide invaluable research support in stream and online learning.