AI Seminar Series

AI Seminar Series will explore relevant topics in artificial intelligence and invite industry speakers and researchers to share their knowledge, experience and success - promoting transdisciplinary AI research and collaboration.

 

 

Contacts

Dr Miao Xu

A Non-Factoid Question-Answering Taxonomy

9 November 2022 1:00pm2:00pm
Join us as we discuss the first comprehensive taxonomy of NFQ categories and the expected structure of answers.

Leaky Deltas: Exposing Data Updates in Natural Language Models

24 October 2022 1:00pm2:00pm
To continuously improve quality and reflect changes in data, machine learning applications must regularly retrain and update their core models. This seminar will show that a differential analysis of language model snapshots before and after an update can reveal a surprising amount of detailed information about changes in the training data. To demonstrate the leakage due to updates of natural language models, we develop two metrics — differential score and differential rank. The extent of leakage analysis that is possible using these metrics across a range of models and datasets will be discussed as well as the privacy implications of the findings, mitigation strategies, and evaluation of their effect.

AI in Energy: Challenges and opportunities in grid integration

13 October 2022 1:00pm2:00pm
This talk will discuss approaches to integrating behind-the-meter distributed energy resources (DER) into low-voltage distribution networks. We approach the problem from two angles: (i) uncoordinated energy management of individual prosumers and (ii) coordinated approaches that orchestrate the response of several prosumers in virtual power plants.

The anatomy of an AI system for misinformation detection and where humans fit in it

25 August 2022 3:00pm4:00pm
Information warfare instruments have recently been used to weaponise misinformation to foster propaganda and to reach political goals by influencing populations at scale. In this seminar we will discuss how human-in-the-loop AI technology can support expert fact-checking efforts that have been increasing substantially due to the rise in the spread of misinformation.

AI in healthcare – from bytes to bedside

19 August 2022 1:00pm2:00pm
Artificial intelligence (AI), and machine learning (ML) in particular, are set to revolutionise everyday healthcare and improve patient outcomes. This presentation will illustrate the steps required to take AI/ML applications from in-silico prototypes to effective point-of-care instruments embedded within electronic medical records and imaging software.

The Future of Precision Prevention for Advanced Melanoma

27 July 2022 3:00pm4:00pm
Precision prevention of advanced melanoma is fast becoming a realistic prospect, with personalized, holistic risk stratification allowing patients to be directed to an appropriate level of surveillance, ranging from skin self-examinations to regular total body photography with sequential digital dermoscopic imaging.

Explainable AI is dead! Long live explainable AI!

28 June 2022 11:00am12:00pm
Prof. Miller will present an overview of the intersection of explainable AI and will present some key examples of how to integrate social science knowledge into these methods for explainability in sequential decision making problems.

Unloading the Information “Overload” in Intensive Care

22 June 2022 10:00am11:00am
Prof John Fraser will explore how we can thrive in the midst of COVID 19 and provide an overview of the global collaboration of CCRG and the future of ICU.

Revisiting the Breeder’s Equation: Implications of our advancing understanding of trait genome-to-phenome relationships

26 May 2022 3:00pm4:00pm
Plant breeders are expected to have a working knowledge of the Breeder’s Equation. It is also expected that the Breeder’s Equation will be used as a framework to help optimise the design of their breeding program. This was relatively straightforward when breeding was based predominantly on selection for trait phenotypes. Today, breeders either use, or aspire to use, genomic information in many ways to improve the effectiveness of their breeding programs.

Beyond the Paddock: Enhancing food production through the integration of predictive digital agricultural systems

14 April 2022 12:00pm1:00pm
The issues of food security and sustainable agriculture are vital concerns to society and key topics in assessments of climate variability and change on productivity and food supplies. However, accurate and advance knowledge of the associated risk in crop production systems can mitigate some of the impacts of such causative threats. It is anticipated that such approaches will increasingly become more valuable in decision-making and lead to better preparedness in coping with the impact of extreme climate events leading to a reduction in the downside risk and more resilient agricultural food systems.

Agriculture meets AI

17 March 2022 4:00pm5:00pm
Artificial intelligence and the data sciences are enabling ‘Agriculture 4.0’. In 2020, agrifood tech startups raised more than $30 billion in investment. Many of these innovations are deployed in agriculture research, supporting new sustainable solutions that keep us fed. Professor Scott Chapman will discuss some of these digital and predictive agriculture technologies.

Personalised care of musculoskeletal pain: The potential of AI

1 December 2021 4:00pm5:00pm
Musculoskeletal pain conditions, including low back pain, are the leading cause of disability internationally. Recent work has begun to expose features that have the potential to guide personalisation of treatment, but the challenge to disentangle the complexity of the condition is immense. Artificial intelligence will need to play a role.

Bridging the Gap between Text and Knowledge

12 October 2021 4:00pm5:00pm
Sophia Ananiadou will describe NLP methods for the extraction of structured representations from text for downstream applications while addressing challenges of information extraction tasks.

Fairness, interpretability and diverse datasets are not enough – getting specific about algorithmic bias

15 July 2021 3:00pm4:00pm
The concept of "biased data" is often too generic to be useful.  Through a series of cases studies, we will explore what algorithmic bias is, different types (with different causes), and debunk some common misconceptions.  We will cover why algorithmic bias is a problem worth addressing and some steps towards solutions.