Author: Kath Williamson

Industry Placement in PhD Training – A National Study of Student and Advisor Experiences

Posted on by Kath Williamson

New Report Released: Industry Placement in PhD Training – A National Study of Student and Advisor Experiences

How can Australia better prepare PhD graduates for careers across academia, industry, and government?

As industry demand for research-trained professionals continues to grow, industry placements are playing an increasingly critical role in bridging doctoral education and the innovation economy. Yet, until now, insight into what enables successful placements for students, advisors, and host organisations alike, has remained fragmented and incomplete.

We’re pleased to share the release of Industry Placement in PhD Training – A National Study of Student and Advisor Experiences conducted through the ARC Training Centre for Information Resilience (CIRES) with endorsement from the Australian Government Department of Education.

Drawing on perspectives from PhD students and academic advisors across Australia, the report examines:

  • Participation pathways & placement models
  • Student & advisor expectations & experiences
  • Benefits for research translation, professional skills, & career development
  • Challenges relating to workload, supervision, funding, & administration
  • Evidence-based recommendations for universities, industry partners, & policymakers

The findings show that industry placements are a valuable component of doctoral training, helping students apply research in real-world contexts, build professional networks, and develop industry-ready capabilities. At the same time, the report identifies opportunities to strengthen support, alignment, and institutional processes to maximise outcomes for students, universities, and industry partners alike.

Thank you to our report authors: Prof. Shazia Sadiq, Prof. Marta Indulska, Dr. Xianxian Jiang, & Dr. Javad Pool.

Read the full report here.

5th UQ-wide AI HDR Showcase

Posted on by Kath Williamson

The 5th UQ-wide AI HDR Showcase was successfully hosted by the AI Research Network, Alina Bialkowski, CIRES CI Rocky Chen, CIRES Centre Director, Shazia Sadiq & Shane Culpepper on 10-11 June, with 34 student presentations and over 100 attendees. The two-day event brought together students and researchers from diverse fields across the university from business, education, arts, agriculture, medicine, computer science, and engineering, to explore the transformative role of AI. The core theme throughout the showcase was shifting focus from merely using AI, to developing essential human skills; with speakers emphasising that while AI excels at generating answers, humans must possess superior critical thinking, and the ability to define the right questions.

There were many amazing contributions, including from Rocky Chen, Paul Vrbik, and Aneesha Bakharia in our School. Highlights included Pierre Benckendorff’s (Deputy Dean, Grad School) opening address on HDR skills and research culture, Stefan Hajkowicz’s (Chief Research Consultant, CSIRO) keynote on future “purple skills”, Sophia Arkinstall’s (Founder, AI & Society) talk on AI Literacy, the AI Expert Panel discussion chaired by Rocky Chen with EECS’s Paul Vrbik and EECS PhD graduates (Aninda Saha, Ashleigh Richardson, Shengyao Zhuang) contrasting different relationships with AI in work and life from managing AI agents, to preventing people from blindly trusting AI, and Aneesha Bakharia’s hands-on Vibe-Coding workshop, during which students built their own practical research apps.

The showcase celebrated student creativity and dedication through multiple award categories, with EECS’s Feng Luo winning People’s Choice Best Presentation. Thanks to the EECS judges and attendees! Full summary and photos of the event are available here.

Welcome to Postdoctoral Research Fellow, Lufan Zhang

Posted on by Kath Williamson

Welcome to The University of Queensland, Lufan Zhang!

We are delighted to announce the appointment of Lufan Zhang as our new Postdoctoral Research Fellow. Lufan is one of our very own, having recently submitted her PhD thesis for examination at Swinburne University of Technology, supervised by CIRES Chief Investigator Associate Professor Paul Scifleet.

Her doctoral research was conducted in collaboration with partner organisation Astral, reflecting her strong engagement with industry-relevant, applied research.

“Undertaking my PhD with the support of CIRES at Swinburne, in collaboration with Astral Consulting, has been an incredibly rewarding and enriching journey. The industry-focused partnership offered invaluable real-world insights and created a dynamic environment that fostered both my academic development and professional growth. I am deeply grateful to everyone who supported and guided me along the way, and I am excited for the opportunity to continue exploring, innovating, and contributing to the field,” said Lufan.

At UQ, Lufan will join the CIRES team to contribute to innovative research on AI preparedness and the evaluation of AI deployments across public and private sector organisations. She will work closely with CIRES Director Professor Shazia Sadiq FTSE and Research Director Professor Marta Indulska on advancing impactful, responsible AI research.

“Lufan brings extensive experience in empirical research methods and working with industry. She is well positioned to direct her future research efforts towards AI readiness and I look forward to working with her on the important and interesting research questions in that area,” said Professor Sadiq.

We’re thrilled to have Lufan continue her journey with CIRES and look forward to the insights and impact she will bring.

Welcome Lufan!

 

 

ATSE #FellowFriday Building Resilient Data Futures

Posted on by Kath Williamson

Our Centre Director Professor Shazia Sadiq FSTE is this week’s FellowFriday! Thank you ATSE for profiling Shazia and her amazing work and leadership in data science, AI and responsible data management.

A Professor at The University of Queensland, Professor Sadiq’s research focuses on helping organisations build and protect agile, ethical and resilient data systems for advanced analytics and AI. Her work also addresses the socio-technical barriers that shape successful data-driven transformation. She is Director of the ARC Training Centre for Information Resilience (CIRES) and has been a passionate advocate for ethical educational technology for over two decades.

Professor Sadiq also played an important role in building support for the new Resilient Data Engineering Award joining the ATSE Awards this year. Her leadership helped build strong momentum across the Australian university sector, highlighting the critical work being done to make data safer, more robust and more useable for the benefit of society.

Thank you Professor Sadiq for your leadership and vision in shaping the future of data, AI and responsible technology in Australia and globally.

ATSE Resilient Data Engineering Award Announced

Posted on by Kath Williamson

Celebrating a new award for Australia’s data innovation ecosystem!

CIRES is proud to support the new Resilient Data Engineering Award, launching in 2026 as part of the prestigious Australian Academy of Technological Sciences & Engineering (ATSE) Awards.

This award recognises early career data researchers, professionals and teams who are building the resilient data pipelines that underpin critical national systems and decision making.

CIRES Centre Director Professor Shazia Sadiq FTSE led this initiative in partnership with ATSE, and with fantastic support for the award from heads of computing across Australia.

Information resilience is the ability to build and maintain agile data pipelines that can detect and respond to failures and risks across the entire data lifecycle. Promoting information (or data) resilience among engineers, scientists, and researchers is essential to developing a workforce that can drive a data savvy society, fuel Australia’s future economy, and uphold responsible data management practices.

“This award recognises and celebrates the back-end work done by data scientists and data engineers, work that brings credibility, efficiency, and impact to so many discoveries. It is an exciting opportunity to celebrate the future leaders designing the robust, trustworthy data systems that Australia increasingly relies on,” Professor Sadiq said.

A huge thank you to all the contributing partners:

  • The University of Queensland
  • Adelaide University
  • Monash University
  • The Australian National University
  • The University of Western Australia
  • UNSW
  • University of Melbourne
  • Australasian Computing Research and Education (CORE)
  • ARC Training Centre for Information Resilience (CIRES)

Help put the spotlight on the next generation of resilient data innovators. Please spread the word – applications will open on 10 March and close on 12 May 2026.  Full details and guidelines available on the ATSE website.

Agentic AI in Financial Services

Posted on by Kath Williamson

On 26 January, in collaboration with scientists from CommBank and NUS, CIRES Chief Investigator, Dr Rocky Chen, and Dr Joel Mackenzie organized a workshop “Agentic AI in Financial Services” at the AAAI’26 conference in Singapore. This workshop aimed to promote recent advances in the intersection of Agentic Systems, FinTech, Information Retrieval, and Personalized Recommendation. The workshop featured oral and poster presentations of accepted papers, as well as three keynotes given by Machine Learning/FinTech experts Feng Liu (UniMelb), Hari Suresh (Nvidia), and Guansong Pang (SMU), and was well-attended by 55+ delegates on the day. Notably, among the 224 authors of 22 accepted papers, 35.3% are industry-affiliated, including those from BlackRock, JP Morgan, VISA, and Alibaba – the financial industry sector is putting real investments in agentic FinTech systems!

Back to School

Posted on by Kath Williamson

Earlier this month, CIRES Centre Director, Professor Shazia Sadiq, had the honour of being invited to her old high school – ICG:Islamabad College for Girls.

“It was so much more than a trip down memory lane. This is a state school, with free education for over 6000 girls. It was much smaller when I was there! The calibre of the students (check out the podcast) and the dedication of the staff was nothing short of inspirational. Such examples, especially in a developing country like Pakistan, give me lots of confidence in our future leaders. Go ICG! And a shout out to the many collaborators I have the privilege of knowing, who are champions of girls’ education and women in technology.

Some years ago, I had come across the work of Paul Hawken and the Drawdown project where the ‘Analysis of 125 countries shows that education (particularly female education) is the single most important socioeconomic factor associated with a reduction in vulnerability to natural disasters.'”

Postdoctoral Research Fellow position at UQ

Posted on by Kath Williamson

Applications close 1st February 2026

We are recruiting for a Level A postdoc fellow to join us in the ARC Training Centre for Information Resilience (CIRES) at The University of Queensland in sunny Brisbane, Australia. 

This position will contribute to cutting-edge research on AI preparedness and the evaluation of AI deployments across public and private sectors. You’ll develop frameworks to assess organisational and data barriers to AI adoption, evaluate implementation outcomes, and analyse the impact of emerging AI policies, standards, and governance guidelines.

This role is mainly based at the ARC Training Centre for Information Resilience (CIRES) at The University of Queensland working closely with leading experts and industry partners. You’ll be supported by senior academics with opportunities for increasing autonomy over time.

We are seeking a candidate with:

  • Completion or near completion of a PhD in Computer Science, Data Science, Information Systems or a related field.
  • Demonstrated expertise in empirical methods, proficiency in data analysis, and deep knowledge of contemporary AI tools and techniques
  • Experience in conducting research projects, demonstrating high-level written and oral communication skills.
  • Peer-reviewed publications in high-impact journals or premiere conferences.
  • Ability to work both independently and as a member of a cross-disciplinary research team.

See the full position description and how to apply:

Applications close Sunday 1 February 2026 at 11:00pm AEST.

This position will be based in the Australian Research Council (ARC) Industrial Transformation Training Centre for Information Resilience (CIRES) at UQ, and working across multiple projects with industry and government partners, providing a wealth of experience in multi-disciplinary teams, research planning, and industry and public sector dynamics. The successful candidate will have the opportunity to work directly with the Centre’s partners, with an expected third of their time dedicated to working with partner organisations.

Questions? For more information about this opportunity, please contact Professor Shazia Sadiq and Professor Marta Indulska.

CIRES @ AJCAI-25: Towards Resilient AI Systems

Posted on by Kath Williamson

Great experience representing CIRES at AJCAI 2025 in Canberra!

On 2 December, CIRES hosted both a workshop and a panel discussion on resilient and responsible AI systems. A special highlight was having Dr Yanbin Liu join our panel, his insights added great depth to the discussion!

Thanks to Xuwei (Ackesnal) Xu, Haodong Hong and Zhuoxiao Chen for their excellent presentations, and to everyone who attended our workshop.

And special thanks to organiser, CIRES Postdoctoral Researcher, Dr Zixin Wang, for her dedication and excellent coordination.

UQ Guide on Responsible Use of Generative AI in Research

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CIRES Centre Director, Professor Shazia Sadiq contributed to creating the UQ Guide on Responsible Use of Generative AI in Research, available to all staff at The University of Queensland. The Guide outlines risks and opportunities across the research lifecycle—idea generation, literature review, hypothesis development, coding, data analysis, manuscript preparation, and visualisation. It includes discipline-specific examples, guidance for grant applications (ARC/NHMRC), disclosure requirements, and an appendix on data handling, copyright, and privacy implications.

UQCEAI Workshop: Proof of Concept to Production for Enterprise AI

Posted on by Kath Williamson

On 12th November 2025, the UQ Centre for Enterprise AI hosted the workshop “Getting from Proof of Concept to Production for Enterprise AI.” With over 50 participants joining from industry, government, and academia, the conversation focused on the systematic challenges facing organisations in implementing Enterprise AI at scale, and the key measures to consider when evaluating success in AI adoption and integration. The panel discussion moderated by Nicole Hartley focused on unlocking AI value beyond POC and what it takes to get there. Panel members were Ryan van Leent (SAP), Nathan Bines (Qld Gov’t), Ida Asadi (UQBS) and Joel Mackenzie (EECS), with the event led by CIRES Centre Director, Prof Shazia Sadiq, and CIRES Centre Research Director, Prof Marta Indulska (photo below). More details here and you can find out more about the Centre here.

QPS Partner at International Association of Chiefs of Police Conference

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CIRES Partner Investigator and Queensland Police Service (QPS) staff, Mr Nicholas Moss, attended the International Association of Chiefs of Police (IACP 2025) Annual Conference and Exposition in Denver Colorado USA, 18-21 October 2025. Nicholas presented results from the CIRES-QPS project on community-engagement on the use of data. This project aims to understand community attitudes towards data analytics, particularly in policing.

UQ AI Conference Dry Run Seminar Series

Posted on by Kath Williamson

CIRES Centre Director, Professor Shazia Sadiq, participated as a panelist at the:

UQ AI Conference Dry Run Seminar Series

(Part of EECS Data Science Discipline HDR Student Support)

📍 Date & Time: October 13, 2025, 1:00–4:00 PM

📍 Location: 46-402 Seminar/Board Room (Andrew Liveris Building)

About the Event…

The UQ AI Conference Dry Run Seminar Series is an initiative launched by the UQ EECS Data Science Discipline to support our HDR student community. This inaugural event marks the beginning of a recurring seminar series designed to help our students shine on the global stage.

The goals of the series are to:

  • Practice presentations: Give HDR students the chance to rehearse their talks for top international conferences
  • Receive constructive feedback: Present in a supportive environment and gain insights from peers and faculty that can sharpen delivery and content.
  • Showcase UQ research: Share cutting-edge work with a broader audience, raising the visibility of the exciting contributions coming from UQ.
  • Build community: Strengthen connections across research groups and foster collaboration through shared discussion and networking.

Format: 10-minute presentation + 5-minute Q&A session

This series will serve as a training ground for students preparing to present at major venues, while also offering the UQ community a front-row seat to the innovative AI research being developed within our faculty.

UQ-UZH Symposium and Public Lecture

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On 7-8 October, CIRES CI Professor Gianluca Demartini participated in the UQ-University of Zurich (UZH) Symposium: Challenges and Opportunities for Social and System Change, presenting an update on the joint UQ-UZH project on Digital Deliberative Democracy (d3-project.ch) funded by the Swiss National Science Foundation, and as well as serving as the expert responder for the UQ-UZH public lecture A Toolbox for Human-AI Collaboration in Lifespan Health Analysis.

Empowering Learners in the Age of AI

Posted on by Kath Williamson

On 8 October, CIRES CI A/Prof Hassan Khosravi moderated a panel  as part of the free 2025 on Empowering Learners in the Age of AI.

Hassan moderated this panel with Professor Jason M. Lodge (The University of Queensland), Dr Aneesha Bakharia (The University of Queensland) and Peter Xing (Microsoft) as distinguished panellists, bringing deep expertise and diverse perspectives to this important conversation.

Why this matters
The use of Large Language Models (LLMs) has demonstrated clear performance gains for students. Yet performance is only part of the story. Scholars caution that polished outputs may come at the expense of genuine learning, as students risk offloading critical thinking and problem-solving to AI. This panel explores how we can move beyond productivity to design AI learning companions that prioritise learning gains over performance gains, nurturing curiosity, understanding, and deeper engagement. 

Paper: Understanding failures in health data protection

Posted on by Kath Williamson

Many health data breaches aren’t just caused by hackers. Inadequate processes and irresponsible use of health data often create opportunities for serious cybersecurity incidents. In our study, experts recounted staff admitting, “I didn’t know, nobody told me,” or using personal Gmail for sensitive communications. One cybersecurity expert observed, “[Healthcare ecosystems] are not good at these things [data protection by design]. We say that they don’t bake in security; they just bake the cake and spray on some [cyber]security.”

Our mixed-methods study, published in Behaviour & Information Technology (open access explored these critical vulnerabilities in health data protection. We gathered insights from cybersecurity and privacy experts across 14 countries, including CISOs, IT security officers, researchers, privacy managers, and Data Protection Officers.

We identified 30 failure factors and, using the People-Process-Technology framework, unpacked the top seven:

  • People: non-compliant behaviour, and lack of cybersecurity awareness
  • Process: inadequate risk management, weak data integrity monitoring, and a lack of breach response and recovery plans
  • Technology: unsecure third-party applications, and a lack of data protection by design

These factors often interlink, creating complex vulnerabilities. With the growing adoption of big data analytics and AI in healthcare, understanding these failure points is crucial. Our model offers actionable insights for healthcare organisations to strengthen data protection, develop mitigation policies, and reduce the risk of breaches, ensuring safer care and maintaining trust.

Towards a model for understanding failures in health data protection: a mixed-methods study, Javad Pool, Saeed Akhlaghpour, Farkhondeh Hassandoust, Farhad Fatehi & Andrew Burton-Jones

AI Horizons – Conversations with Australia’s leading and emerging researchers

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On 22 September, CIRES Centre Director Prof. Shazia Sadiq FTSE hosted AI Horizons – Conversations with Australia’s leading and emerging researchers, an inspiring event organised by the Australian Academy of Technological Sciences & Engineering (ATSE). The event brought together brilliant minds in AI—from established experts to rising stars—to explore the future of artificial intelligence in Australia.

Speakers: Dr Sue Keay FTSE UNSW AI Institute, Dr Scarlett Raine & Prof. Michael Milford FTSE QUT Centre for Robotics, & Hung Lee & Distinguished Prof. Svetha Venkatesh FTSE FAA Deakin University.

Watch on YouTube: AI horizons – Conversations with Australia’s leading and emerging researchers

 

 

Research Insight: New Approach for Irregular Time Series in Healthcare AI

Posted on by Kath Williamson

EMIT: A New Approach for Irregular Time Series in Healthcare AI

Excited to share our paper “EMIT: Event-Based Masked Auto Encoding for Irregular Time Series” published at ICDM 2024. Together with A/Prof. Sen WANG, Dr Ruihong Qiu, A/Prof. Adam Irwin and Prof. Shazia Sadiq, we explore how irregular time series (like vital signs and lab results recorded at uneven intervals) challenge existing AI models and how our proposed framework, EMIT, improves clinical decision support through better representation learning. Special thanks to CIRES, Queensland Health and The University of Queensland for supporting this research.

Read full paper at https://arxiv.org/pdf/2409.16554

 

Our Approach
We introduce EMIT, a pretraining framework based on transformer architecture, tailored for irregular clinical time series data. EMIT learns by:

  • Finding important points in irregular time series
  • Pretraining by masking and predicting those points
  • Use the pretrained model for any downstream task (e.g., outcome prediction)

Key Findings

Improved Representation Learning: EMIT captures important variations without losing timing information, outperforming generic pretext approaches for irregular time series.

Data Efficiency: On benchmark healthcare datasets (MIMIC-III & PhysioNet Challenge 2012), EMIT achieved strong results using only 50% of labeled data, reducing reliance on costly annotations.

Task Relevance: By designing pretext tasks specific to irregular time series, EMIT delivers more reliable clinical predictions compared to standard forecasting approaches.

How can we design AI that adapts to the messy, irregular reality of clinical data while still delivering trustworthy predictions?