Date [16 Feb 2022]

Edge AI Frontiers Models, Systems and Applications

at [AJCAI 2021 Workshop Online]

Event Recording: https://webcast.csiro.au/#/videos/c4b210c3-dcad-4b62-8c0e-d105bd71369c

Relevant Areas

Enabling technologies such as knowledge distillation, model quantisation, and neural architecture search for edge AI
Industrial use cases, case studies, operationalisation of edge AI-centric systems and their impacts to Australia
Edge AI devices and software tools
Self/semi/weak supervised learning on edge devices

Keynote Speakers

Sara Beery

Caltech

Senior PhD candidate in Computing and Mathematical Sciences at Caltech

Dr Sue Keay

Robotics Australia Group

Founder and Chair of Robotics Australia Group

Prof Xiaojun Chang

University of Technology Sydney

Professor in Australian Artificial Intelligence Insitute, University of Technology Sydney

Dr Brano Kusy

CSIRO

Principal Research Scientist and Group Leader of the Distributed Sensing Systems in CSIRO

Prof Chunhua Shen

Zhejiang University

Professor in Chinese State Key Lab of CAD&CG, Zhejiang University

Dr Lars Petersson

CSIRO

Group Leader and Senior Principal Research Scientist in Imaging and Computer Vision Group, CSIRO

A/Prof Jun Zhou

Griffith University

Associate Professor in School of Information and Communication Technology at Griffith University

Khanh LeViet

Google Inc.

TensorFlow Developer Advocate at Google, Edge AI expert

The goal of this workshop is to connect people and share knowledge in the area of edge AI.

ML/AI has become a big part of the technological innovation in recent years. Although they prove powerful in many applications where power constraints are non-existence and network connectivities are always available, in real-life situations, a large limiting factor for their usefulness is still the resources needed to deploy such systems. This workshop brings together passionate researchers and industrial practitioner together to discuss the gaps and R&D efforts to address them.

Australia is committed to building AI capabilities and making them accessible to the public so everyone in the society can benefit from it. Right now there are technical gaps in making AI more ubiquitous so they are more feasible in real-life applications. There are also knowledge gap where domain practitioners without a non-technical background have difficulties to grasp the capabilities, limitations of edge AI and its feasibility to support their use case. This workshop, by connecting people from scientific research, engineering, and domain applications, builds bridges to share knowledge and experience in this area.