Jordan Shipard

Efficient Subnets for Scalable Onboard AI in Space

Queensland University of Technology

Jordan Shipard completed a Bachelor of Engineering (Honours) and a Bachelor of IT from the Queensland University of Technology (QUT) in 2021, majoring in Mechatronics and Computer Science. During his final undergraduate year, Shipard worked remotely part-time for BAE Systems in Cairns while conducting research relating to neural architecture search in partnership with Sentient Vision Systems. Instead of continuing with BAE, Shipard decided to purse an interest in Artifical Intelligence (AI), undertaking a PhD with the Signal Processing, Artificial Intelligence and Vision Technologies (SAIVT) Lab at QUT. His research focuses on developing a method for training AI across a constellation of satellites for Earth observation tasks, requiring topics of AI research relating to federated learning, few-shot learning, vision-language models, and efficient transformer models.

Project Title: Efficient Subnets for Scalable Onboard AI in Space

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