Latest events

AIML Connect Fridays: Coded Bias Screening

Date: Fri, 18 Jul 2025, 4:00 pm - 5:30 pm
Location: Tech Central, Lot Fourteen

AIML and the Lot Fourteen Innovation District presented a screening of Coded Bias, a documentary about artificial intelligence and the biases that can be embedded within. When MIT Media Lab researcher Dr Joy Buolamwini discovers that facial recognition does not see dark-skinned faces accurately, she worked to find out why these systems failed. After discovering that facial recognition programs only worked for her when she wore an actual white mask, she went on to research how else tech systems can affect minorities and embarks on a journey to push for the first-ever U.S. legislation against bias in algorithms that impact us all.

AIML Research Seminar: Protecting SAR Imagery from Adversarial Attack Using a Diffusion Model

Date: Wed, 16 Jul 2025, 10:30 am - 11:30 am
Location: AIML

Efficient wide-area surveillance of the maritime environment requires automated detection and classification techniques. Deep learning can be exploited for this purpose, but it is susceptible to adversarial attacks that can cause misclassifications. Diffusion models have previously been shown to improve robustness against adversarial perturbations in electro-optic imagery. This work investigates how such adversarial defence techniques perform against white-box attacks on a high-resolution Synthetic Aperture Radar (SAR) dataset. Using a maritime SAR dataset, we demonstrate the benefits of applying a diffusion model, including improved classification performance and reduced sea clutter.

AIML Research Seminar: Creating a Video Narrative From a Text-based Screen Play

Date: Tue, 1 Jul 2025, 10:30 am - 11:30 am
Location: AIML

In this session, Sam Hodge, AIML Machine Learning Engineer, explains the process of using synthetic actors to perform dialog specified in a screen play using a combination of audio and 3D speech synthesis and then overcoming the “uncanny valley” sensation through stylisation with ongoing work toward photorealism.

AI on the Ground Seminar: What if you could start over with what you know now?

Date: Fri, 27 Jun 2025, 10:30 am - 11:30 am
Location: AIML

This session explores the transition from academic AI prototypes to operational systems within clinical environments. Drawing from experiences at SickKids and now Seattle Children’s, this strategic and reflective talk will share key insights from previous successes and failures, with the goal of fostering dialogue and community learning around applied clinical AI.

AIML Connect Fridays: Bombshell – The Hedy Lamarr Story

Date: Fri, 20 Jun 2025, 4:00 pm - 5:30 pm
Location: AIML

Join us for AIML Connect Fridays to watch Bombshell – The Hedy Lamarr Story. In this documentary, discover the untold story of Hedy Lamarr: Hollywood star, scientific visionary, and the woman behind one of the most valuable technological breakthroughs of the 20th century.

AIML Research Seminar: Adversarial attacks against machine learning models for satellite imagery

Date: Tue, 3 Jun 2025, 10:30 am - 11:15 am
Location: AIML

Satellites utilise a wide range of sensing modalities to collect data for applications such as earth observation, navigation and disaster management. Hyperspectral imagery is one such modality that captures a detailed spectral response of scenes across the electromagnetic spectrum. This type of imagery, however, generates vast amounts of data which requires processing to extract meaningful insights. To permit real-time decision making, edge computing – performed directly onboard a satellite – is used to process data before transmission to ensure only essential data is downlinked, ensuring fast response times. This is critical for time-sensitive applications including disaster detection and military surveillance. Deep neural networks (DNNs) are increasingly being used to automate this processing onboard satellites due to their ability to detect objects and anomalies faster and more accurately than traditional methods. However, DNNs are susceptible to adversarial attack. These attacks involve placing engineered objects into the scene of an image that cause deep neural networks to produce incorrect outputs. This research explores the vulnerability of DNNs to adversarial attack in satellite imagery and investigates methods to enhance the reliability of DNNs in the presence of such threats.

Centre for Augmented Reasoning (CAR) Legacy Event

Date: Fri, 30 May 2025, 9:00 am - 5:30 pm
Location: AIML

The CAR Legacy showcased the achievements and impact of the Centre for Augmented Reasoning, a significant initiative funded by the Australian Government Department of Education in 2021, which helped transform Australia's capability in Machine Learning and Computer Vision.

CMS Research Seminar: Provable Security and Verification – From Theory to Practice

Date: Thu, 29 May 2025, 1:15 pm - 3:00 pm
Location: Ingkarni Wardli

In this talk, Professor Ioana Boureanu gave an overview of her work that covered aspects of cryptographic models and proofs, as well as logic-based formal verification for security and privacy, primarily in cryptographic protocols. Professor Boureanu discussed theoretical developments as well as applied verification, highlighting their impact on standardisation processes, for instance in the payments industry and mobile networks.

Stone & Chalk Ecosystem Mixer in Artificial Intelligence

Date: Fri, 23 May 2025, 4:30 pm - 6:30 pm
Location: Stone & Chalk

The packed event was held at Stone & Chalk and was an opportunity for some of the smartest, most innovative minds in the Australian AI space to come together to network and have a bit of fun. The gathering featured tech demonstrations, limitless opportunities for collaboration, and a spirited discussion on responsible AI from AIML's own Professor Javen Qinfeng Shi, Interim Director of the Responsible AI Research Centre (RAIR).

AIML Research Seminar: VSLAM-LAB – A Comprehensive Framework for Visual SLAM Baselines and Datasets

Date: Tue, 20 May 2025, 10:30 am - 11:15 am
Location: AIML

Visual SLAM (Simultaneous Localization and Mapping) research is often hindered by fragmented toolchains, inconsistent evaluation protocols, and complex system setups. In this seminar, Dr. Alejandro Fontan will present VSLAM-LAB, a unified and extensible framework designed to streamline the development, benchmarking, and deployment of Visual SLAM systems. VSLAM-LAB simplifies the end-to-end SLAM pipeline—from automated dataset downloading and formatting to standardized experiment execution and trajectory evaluation—using a single command-line interface. The framework supports a wide array of state-of-the-art SLAM methods and datasets, enabling reproducible research and facilitating fair, comprehensive comparisons.

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