I am a Research Fellow in Computer Science at the University of Waikato, New Zealand, working within the AI Institute. My research focuses on Automated Machine Learning (AutoML) for evolving data streams, including dynamic hyperparameter optimisation, online and continual learning, concept drift adaptation, streaming regression, and adaptive anomaly detection. My work combines academic research with practical AI engineering and open-source software development.

Research. My doctoral research focused on Automated Machine Learning for Evolving Data Streams, investigating how machine learning systems can automatically configure, tune, and adapt themselves as data arrives continuously and its underlying distribution changes. I develop methods for streaming AutoML that operate under computational, memory, and latency constraints while adapting to concept drift and changing environments.

Industry. I have experience as an AI developer and researcher across AI platforms, SaaS products, automotive analytics, natural language processing, and AI for regional languages. My work spans the complete AI development lifecycle, from research and experimentation to engineering, deployment, and production systems.

Open Source. I actively build and maintain open-source AI and machine learning software that has collectively reached 100K+ downloads across platforms, making research and applied AI tools accessible to practitioners, researchers, and developers.

• TuiML — machine learning for humans and AI agents.
• Weka.ai — a modern, browser-based machine learning workspace built around Weka.
• EngramX — an open-source memory framework for AI agents.
• LLMPrice — fast, offline-first LLM pricing lookup for 2,500+ models in Python and TypeScript.
• ZeroLLM — simplified local LLM inference with automatic hardware detection.
• DeepImageSearch — AI-powered image search supporting text-to-image, image-to-image, and hybrid retrieval.
• DeepTextSearch — multilingual text embedding, semantic search, and reranking.
• SSEM — lightweight semantic evaluation metrics for LLMs and AI agents.
• Autowave — simple audio classification in Python.