Latest events

AIML Community Day 2024

Date: Sat, 26 Oct 2024, 12:00 pm - 4:00 pm
Location: Gold Escort, Belair National Park

AIML Community Day was an opportunity for our members to gather together to enjoy the beautiful scenery at Belair National Park. It was wonderful to see so many staff, students, and their families enjoying the sunshine, good food, and AIML camaraderie. Networking and even frisbee tag were on tap for all in attendance.

AI on the Ground Seminar: Building a responsible ecosystem for AI in health

Date: Fri, 25 Oct 2024, 10:30 am - 11:30 am
Location: AIML

We were honoured to welcome Assoc Prof and Prof from the to the as speakers for our first AI on the Ground seminar, focusing on building a responsible artificial intelligence (AI) ecosystem for the health sector.

Get Science Media Savvy! AusSMC Media Training for Scientists

Date: Thu, 24 Oct 2024, 2:00 pm - 4:30 pm
Location: AIML

The Science Media Savvy workshop is designed to increase your confidence and give you the knowledge and media skills to help you engage more effectively with the wider public through the media.

AIML Research Showcase 2024

Date: Wed, 16 Oct 2024, 10:00 am - 6:00 pm
Location: National Wine Centre of Australia

The AIML Research Showcase 2024 brought together members, industry partners, and other invited stakeholders to share the latest research from the AIML community. The event featured a keynote address by Associate Professor Angela Yao, Computer Vision and Machine Learning Lead at the National University of Singapore. Throughout the day, attendees explored presentations across various AI fields, and the poster session provided early career researchers with a platform to showcase their projects.

AIML Research Seminar: Unlocking the Full Potential of AI in Video Surveillance Overcoming Cost and Accuracy Challenges

Date: Tue, 15 Oct 2024, 10:30 am - 11:15 am
Location: AIML

Abstract: The application of AI for real-time video analytics has the potential to revolutionize video surveillance, enhancing safety, compliance, and convenience for all. However, this promising advancement also presents formidable challenges, primarily centered around cost and accuracy. One pressing concern is the substantial computing resources required to run AI models, particularly in large-scale scenarios with thousands of cameras. The scale of computation can become a significant barrier, necessitating the development of AI inferencing pipelines for high throughput processing. Moreover, deploying a single fixed AI model for all surveillance scenes introduces the risk of numerous errors and inaccuracies. Consequently, post-deployment model improvement becomes a crucial requirement to meet the diverse demands of varying surveillance environments.

AIML Special Presentation: Developing a Novel Social Media Big Data Analytics Approach for Optimising Reverse Logistics Decision-Making

Date: Fri, 4 Oct 2024, 2:30 pm - 3:30 pm
Location: AIML

This session will explore a novel approach that integrates deep learning and social media analytics to enhance reverse logistics decision-making. The primary challenge lies in the need to reduce waste and optimize the reuse and recycling of returned goods by effectively incorporating customer feedback—often overlooked in traditional reverse logistics frameworks.

Main Sequence Visits AIML

Date: Wed, 2 Oct 2024, 10:30 am - 11:30 am
Location: AIML

We were delighted to welcome Danielle Haj-Moussa and Jun Qu from Main Sequence to AIML for an insightful session on venture capital and deeptech business management.

AIML Research Seminar: Pre-showcase Poster Session

Date: Tue, 1 Oct 2024, 10:30 am - 11:15 am
Location: AIML

In advance of the 2024 AIML Research Showcase, our Postdoctoral Research Fellows Dr Paul Albert, Dr Fred Zhang and Dr Yangyang Shu presented their research posters digitally for the AIML community.

ARC Grant Writing Workshop

Date: Mon, 30 Sep 2024, 2:30 pm - 4:30 pm
Location: AIML

This session is designed specifically for Early to Mid-Career Researchers (EMCRs) looking to enhance their grant writing skills. The workshop will be led by Natalie Betts, a grant writing expert with extensive experience. Natalie's career has spanned various fields, providing her with invaluable experience in grant preparation. She spent 2.5 years as a management consultant at McKinsey & Co, learning about strategic positioning, decision-making, and budget modelling. She also worked for 6 years as a part-time technical writer for a medical device company and spent 10 years as a postdoctoral researcher at the Waite Campus, writing her own grants and papers. For the past 7 years, Natalie has been working as a grant editor, with the last 4 years in a full-time freelance position.

AIML Research Seminar: Robust Fitting on a Gate Quantum Computer

Date: Tue, 17 Sep 2024, 10:30 am - 11:15 am
Location: AIML

Abstract: This talk will introduce our paper recently accepted as Oral to ECCV2024. Gate quantum computers generate significant interest due to their potential to solve certain difficult problems such as prime factorization in polynomial time. Computer vision researchers have long been attracted to the power of quantum computers. Robust fitting, which is fundamentally important to many computer vision pipelines, has recently been shown to be amenable to gate quantum computing. The previous proposed solution was to compute Boolean influence as a measure of outlyingness using the Bernstein-Vazirani quantum circuit. However, the method assumed a quantum implementation of an L-infinity feasibility test, which has not been demonstrated. In our paper, we take a big stride towards quantum robust fitting: we propose a quantum circuit to solve the L-infinity feasibility test in the 1D case, which allows us to demonstrate for the first time quantum robust fitting on a real gate quantum computer, the IonQ Aria. We also show how 1D Boolean influences can be accumulated to compute Boolean influences for higher-dimensional non-linear models, which we experimentally validate on real benchmark datasets. This talk is intended for a computer vision audience with minimal quantum physics background.

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