Jie Lu AO

Advanced Machine Learning for Decision Support in Complex Environments

This talk will present how advanced machine learning can effectively learn from complex data to support data-driven decision-making in uncertain and dynamic environments. It will introduce new autonomous transfer learning theories, methodologies, and algorithms that enable knowledge transfer across multiple source and target domains through latent-space construction, mapping functions, and self-training mechanisms.

The talk will also discuss new approaches to concept drift detection, understanding, and adaptation for continuously evolving data stream environments. These methods aim to identify when, where, and how drift occurs, enabling timely and adaptive responses. The presentation will further highlight real-world applications across multiple industry sectors, demonstrating how these advanced machine learning capabilities significantly strengthen prediction and decision support systems.