25 July - 25 July 2024
NextGens Melbourne Fireside Chat 2024
Thu. 25 July 2024
6.00pm - 8.30pm
WSP Melbourne - Level 11/567 Collins St, Melbourne VIC 3000
Register Now
Join the ITS Australia NextGens, in collaboration with iMOVE and WSP for a fireside chat style event on Data and AI.
AI is having a large impact on transport in many diverse areas and it remains an area that is advancing rapidly. With this rapid development comes uncertainty and questions as well as progress. This event will hear from expert speakers who are implementing AI in different ways to improve the way we move. This includes benefits and challenges associated with the use of AI for better management of our road networks and applying AI to connected and automated vehicles. Our line-up of panelists includes:
Dave Rawlinson, Lead Data Scientist, WSP will present "What AI can’t do – essential knowledge for safer use of AI”.
- Focussing the problem and not technology
- Types of data AI can deal with (e.g. unstructured text), vs other types of model
- Mitigation strategies for common problems (including bias, and AI overconfidence)
- Strategies for combining AI with other ML / statistical models, including causality
Yijie (Iris) Su, iMOVE PhD Student, Swinburne University of Technology will present "Transformative commercial urban delivery solutions".
- Presentation based on Yijie's PhD project
- This research aims to identify and evaluate new solutions for commercial urban deliveries to meet the demand of last-mile and surging e-commerce markets.
Saeed Asadi Bagloee, PhD, AI lead, Melbourne School of Engineering, The University of Melbourne
- Dr Bagloee leads an AI team at unimelb, in Prof Sarvi's lab under the AIMES initiative
- The presentation will focus on his work in advancing AI techniques in general and deep learning in particular for transport applications.
Please join us for an educational and collaborative discussion, and networking with others from the industry.
Speakers
David Rawlinson
Lead Data Scientist / WSP
David Rawlinson has more than 20 years’ experience in applied machine learning (ML) and AI, especially industry R&D. He has a BSc in computer science and AI from the school of Cognitive Sciences at Sussex University, UK, and a Phd in Computer Vision and robotics from Monash University in Australia.
David has co-authored many peer-reviewed articles in signal processing, computer vision, tracking, bioinformatics, medical imaging, and the fundamentals of neural networks including few-shot, continual learning and backpropagation. To help educate scientists and engineers on the use of Causality in ML he maintains the https://CausalWizard.app website.
Yijie (Iris) Su
iMOVE PhD Student / Swinburne University of Technology
Yijie (Iris) Su is a final-year PhD candidate at Swinburne University, specialising in sustainable urban freight and mobility solutions, drawing from a decade of involvement in the transportation sector. Her research explores and evaluates transformative and feasible solutions that enhance urban delivery practices in the context of major Australian cities.
Saeed Asadi Bagloee
AI Lead, Melbourne School of Engineering / The University of Melbourne
Dr Bagloee leads an AI team at unimelb, in Prof Sarvi's lab under the AIMES initiative, advancing AI techniques in general and deep learning in particular for transport applications.