A time series is simply data tracked over time—like stock prices, patient vitals, or daily sales. From forecasting retail demand and hospital patient arrival patterns, to identifying breakdowns in machines as they occur, to evaluating medical scans for diagnostic screening, and detecting risk events in cybersecurity, time series data is pervasive and time series AI is needed everywhere. This free masterclass brings together internationally renowned experts in time series to simplify and de-mystify how AI can be used to transform time series data into smarter forecasts, sharper trend detection, and faster decision-making—helping you spot events, opportunities and challenges before they happen.

Topics:

Time Series Introduction and Classification by Prof Geoff Webb, Monash University
- Introduction to Time Series Data and Applications
- Current State of the Art Methods and Tools in Time Series Classification and Regression
- Real-World Time Series Classification Applications and Case Studies
Time Series Forecasting by Dr Christoph Bergmeir, University of Granada, Spain
- Current State of Play in Forecasting
- Forecasting Using Machine Learning and Deep Learning
- Foundational Models for Forecasting
- Real-World Applications and Case Studies
Time Series Anomaly and Drift Detection by Prof Albert Bifet, University of Waikato, New Zealand
- Current State of the Art in Concept Drift Detection in Evolving Time Series
- Current State of the Art in Anomaly Detection in Evolving Time Series
- Tools and Techniques for Concept Drift Detection and Anomaly Detection
- Real-World Applications and Case Studies

Refreshments and lunch will be provided. Limited places available for in-person attendees.

Speakers:

Prof Geoff Webb

Geoff is a leading AI researcher, ARC Laureate Fellow, and Professor in Monash University’s Department of Data Science and AI. His honours include IEEE Fellow, the Eureka Prize for Excellence in Data Science (2017), major IEEE and PAKDD research contribution awards, and the ICDM 10-year Highest Impact Award (2023). He has also been repeatedly recognised by The Australian Research Magazine as Australia’s top researcher in Bioinformatics, Computational Biology, and Data Mining.

Dr Christoph Bergmeir

Christoph is a María Zambrano (Senior) Fellow in the Department of Computer Science and Artificial Intelligence at University of Granada, Spain, and an Adjunct Senior Research Fellow in the Department of Data Science and Artificial Intelligence at Monash University, Australia. His research is on Machine Learning methods in time series forecasting.

Prof Albert Bifet

Albert is a Professor of Artificial Intelligence at the University of Waikato and Director of the AI Institute. He is an internationally recognized researcher in machine learning for data streams, responsible AI, and open-source software development. His work focuses on adaptive learning, concept drift, and anomaly detection, with applications across finance, cybersecurity, and environmental science.