Latest events

AIML Research Seminar: Pre-showcase Poster Session

Miguel Balbin — Tue, 01 Oct 2024 11:03:52 +0930

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.

Main Sequence Visits AIML

Miguel Balbin — Thu, 03 Oct 2024 11:42:30 +0930

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

Miguel Balbin — Fri, 04 Oct 2024 14:40:03 +0930

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.

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

Miguel Balbin — Tue, 15 Oct 2024 11:17:37 +1030

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 Research Showcase 2024

Miguel Balbin — Mon, 16 Sep 2024 11:50:40 +0930

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.

Get Science Media Savvy! AusSMC Media Training for Scientists

Miguel Balbin — Mon, 28 Oct 2024 15:23:40 +1030

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.

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

Miguel Balbin — Mon, 04 Nov 2024 12:58:18 +1030

We were honoured to welcome Assoc Prof Xiao Liu and Prof Alastair Denniston from the University of Birmingham to the Australian Institute for Machine Learning (AIML) as speakers for our first AI on the Ground seminar, focusing on building a responsible artificial intelligence (AI) ecosystem for the health sector.

AIML Community Day 2024

Miguel Balbin — Mon, 28 Oct 2024 15:32:52 +1030

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.

AIML Special Presentation: From Multi-view 3D CT Volume Reconstruction to 3D Content Generation

Miguel Balbin — Thu, 31 Oct 2024 10:52:09 +1030

Abstract: Reconstructing the geometry of 3D geometry from multi-view images or multiple projections has been a fundamental task in Computer Vision and Medical Imaging. The recent emerging generative-AI technology also offers new capability to generate realistic 3D contents simply from user natural input. In this talk, I will report two of our recent works on 3D reconstruction and 3D content generation. The first work is about how to reconstruct 3D CT volumetric shape from X-ray/CT projections, and the second one is on 3D content creation using pre-trained large-scale diffusion models such as the Stable Diffusion. For the latter, I will cover both 3D single object generation, as well as 3D scene generation from hand drawn sketches.