Thesis Title
Modeling Sequential Ad Behaviours in Online Advertising

Research Description
With the rapid advancements in automated digital media, advertising strategies have evolved to become more personalized and contextually aware. As part of the Australian Ad Observatory project, this research focuses on developing models to analyze and understand the sequential behaviors of automated advertising in digital media environments. By modeling ad sequences, this research will provide insights into how automated advertising shapes user experiences and societal trends, particularly in the context of mobile and dynamic advertising platforms. He has experience in the following research areas: modeling behavior, generating synthetic cross-domain behavior, and human activity recognition.

Supervisors
Prof Flora Salim, University of New South Wales
Prof Daniel Angus, QUT