Data Analytics and Artificial Intelligence Masterclass Program - Program and Speakers
Discover how artificial intelligence and data analytics are transforming risk management and critical control monitoring in high-risk industries. This two-day masterclass provides practical insights into how real-time data and AI can be used to verify critical controls, predict failures, and improve workplace safety.
Program
Day 1: Foundations and Practical Applications in Safety and Risk Management
9:00 AM – 4:30 PM (AEST)
Welcome & Opening Remarks presented by MISHC
Kick-off and overview of the masterclass objectives and structure.
From Data to Decisions: An Introduction to Data Analysis and Machine Learning
Explore the fundamentals of data analytics and machine learning, and how they are transforming decision-making in safety-critical industries.
Morning Break
Managing What Matters: Introduction to Critical Control Risk Management and Verification
Presented by Anthony Deakin
Understand the principles of critical control verification (CCV) and its role in proactive risk management.
Interactive Session: Analysis of Your Current CCV Data Process
Hands-on group activity to evaluate strengths, weaknesses, opportunities, and threats in your current CCV data practices.
Case Study Launch: Real-World Application of CCV Data Analytics
Presented by Peter Standish
Introduction to a practical case study that will be revisited throughout the masterclass.
Lunch Break
The Data Value Chain: From Collection to Competitive Advantage
Presented by Adam Foot
Afternoon Tea Break
Scoping for Success: Dimensions of Safety Data in DA and AI Projects
Learn how to define the scope of a data analytics or AI project, including data types, sources, and quality considerations.
Day 1 Wrap-Up and Reflections
Summary of key takeaways and preview of Day 2.
Day 2: Industry Applications of Artificial Intelligence
Theme: Real-World Impact and Future Directions in Health and Safety
9:00 AM – 4:30 PM (AEST)
Welcome Back & Day 2 Overview
A quick recap of Day 1 and a look ahead at today’s focus on applied AI in industry.
AI in the Real World: Tricks and Traps in Workplace Health and Safety
Presented by Professor Maureen Hassall
Explore the practical challenges, ethical considerations, and common pitfalls when implementing AI in WHS contexts.
Predicting the Future: Applications of Predictive Models in Safety Management presented by Mathew Hancock
Learn how predictive analytics can identify emerging risks and support proactive safety interventions.
Morning Tea Break
Interactive Session: The Application of Predictive Modelling
Interactive session where participants explore opportunities to apply predictive modelling techniques.
Lunch Break
Becoming a Data Detective: Applying DA Tools to CCV Information
Dive into practical tools and techniques for analysing numeric, unstructured, and visual data. Includes a hands-on session with one of the tools.
Afternoon Tea Break
Expert Panel: Navigating the AI Landscape in Industry
Panel discussion with industry leaders and researchers on the practicalities, challenges, and future of AI in safety-critical environments.
Final Wrap-Up and Reflections
Summary of key insights from the masterclass, participant feedback, and next steps.
Speakers
Professor Maureen Hassall
Director, Minerals Industry Safety and Health Centre, University of Queensland
Maureen Hassall is Professor and Director of the Minerals Industry Safety and Health Centre at The University of Queensland. She develops and delivers industry-focused research, training and expert consultancy projects that combine innovative and impactful human-centred design, risk management and safety engineering approaches to produce improve workplace health, safety, and wellbeing performance. Maureen’s academic work is motivated by 18 years working in a range of high hazard industries across a number of different countries. She holds Bachelors degrees in engineering and psychology, a Masters in business administration and a PhD in Cognitive Systems Engineering and is a registered professional and chartered engineer.
Nyssa Nair
Research Fellow and Lecturer at Minerals Industry Safety and Health Centre (MISHC), Sustainable Minerals Institute (SMI), The University of Queensland.
Nyssa Nair is an expert in risk management and hazard identification for industrial processes, with a strong focus on advancing process safety education. Over the past 15 years, she has worked in academia and industry, specialising in risk management, process optimisation, process control and data-driven decision-making.
Nyssa has hands-on industry experience in a Major Hazard Facility processing hydrocarbons for polypropylene production, providing her with a practical foundation for her teaching and research. She currently lectures at The University of Queensland (UQ), with the Minerals Industry Safety and Health Centre (MISHC), delivering postgraduate coursework and industry short courses in process safety and system safety. Her academic work explores the integration of artificial intelligence in chemical engineering, with a particular interest in how emerging technologies can support safer, more resilient industrial operations. Nyssa is passionate about equipping the next generation of engineers with the tools and mindset needed to lead in safety-critical environments.
Dr Nik Rybak
Research Fellow at Minerals Industry Safety and Health Centre (MISHC), Sustainable Minerals Institute (SMI), The University of Queensland.
Nik a machine learning and complex systems researcher at the University of Queensland, leads the Artificial Intelligence Health, Safety, and Environmental Risk Management program at MISHC within the Sustainable Minerals Institute (SMI). With a PhD in computer science, Nikodem’s research spans AI-driven solutions to address the complexities inherent in diverse industries. In the Advanced Data Analytics and AI Masterclass, he will present sessions on introduction to AI, covering video, signal processing, and the latest advancements in generative and reasoning systems. His expertise in the application of AI for risk management and decision support systems offers industry professionals the opportunity to gain critical insights into leveraging state-of-the-art AI solutions to drive innovation and enhance operational efficiency. He leads Artifical Intelligence Health Safety and Environmental Risk Management program.
Anthony Deakin
Glasshouse consulting
Anthony is a highly credentialed operational risk management professional, with extensive experience in high-hazard industries. Anthony is widely regarded as a Thought Leader in the operationalising of critical controls and risk management practices. He was a key contributor to the ICMM Health & Safety Critical Control Management guidelines.
Anthony is the Director of Glasshouse Consulting, an independent consultancy specializing in the design and delivery of safety and operational risk management practices. Anthony is a trusted advisor in critical risk management to several tier 1 mining companies, along with many other companies across a variety of high hazard industries (Energy, Utilities, Construction, Ports, Rail, Agriculture, Healthcare). Prior to moving into consulting Anthony worked for Rio Tinto where he held several roles overseeing group programs relating to safety and risk management, systems and assurance, including the design and deployment of their Critical Risk Management and Process Safety Management programs.
Anthony is passionate about ensuring that safety systems and leadership practices support, not hinder, the safe and efficient execution of work at the front line.
Dr Mathew Hancock
Dr Mathew Hancock is an alumnus of MISHC and has spent the last 20 years developing and applying risk management tools and methods across HSE, major projects, and enterprise-level systems. As an Adjunct Professor with MISHC, he collaborates with the team on advancing causal network analysis and computational reasoning technologies for improved risk management.
In the Advanced Data Analytics and AI Masterclass, Mathew will lead a workshop focused on the real-world application of artificial intelligence, working directly with participants to explore how generative AI and advanced modelling techniques can be applied to their own risk and operational challenges.
Adam Foot
Technological Leader; Mineral Professional; Researcher; Engineer
Adam Foot is passionate about bringing people and technology together as co-workers – to unlock human potential and create social value for a better world. This focus drives his current research into the organisational factors that are consistent with successful, highly reliable technology delivery.
Adam has specialised in aligning people and technology to drive productivity, reduce costs, and improve safety performance – all while increasing social value. He consistently finds ways to build systems that benefit both companies and the communities in which they operate.
He has held senior roles within Rio Tinto and BHP’s Technology and Operational teams, developing and embedding advanced systems. Currently, he works in Hitachi’s global Autonomous Haulage team, supporting operations to understand how autonomy can deliver meaningful site-level value. Adam’s operational expertise and deep understanding of business processes have helped bridge the gap between technology and the frontline – improving performance, cyber security, data storage, accessibility, and system usability.
Adam previously served as a Social Licence Committee Member for AusIMM and led one of the largest branches in Australasia, representing more than 2,300 resource professionals. His leadership helped lift AusIMM’s national profile, drove industry collaboration, and shaped responses to emerging legislation, including industrial manslaughter reforms. He also contributed to the development of the industry’s first Social Value professional standards.
Blending design, engineering, art, and people, Adam ensures operations and products are fit-for-purpose, functional, and user-friendly – a mindset rooted in his early entrepreneurship ventures. From the boardroom to the worksite, he makes sure technology delivers impact to the people who matter most.
Peter Standish
Risk Mentor
Peter Standish is a Consulting Director with Risk Mentor and a seasoned mining engineer with over 30 years’ experience in operational management, risk engineering, and technical innovation. He works directly with client teams to convert operational and safety data into actionable insights that improve productivity, strengthen controls, and drive continuous improvement.
Peter leads the delivery of Control Framework and digital assurance programs across Australia and New Zealand, supporting clients in mining, ports, and the electricity distribution sector. His focus includes validating, digitising, and integrating frontline work processes to build scalable systems that enhance governance and meet regulatory expectations.
He has contributed to global initiatives such as the International Council on Mining and Metals’ Innovation for Cleaner, Safer Vehicles, helping translate strategy into effective site-level practice.
Peter brings a practical, systems-based perspective on how data, people, and process can be aligned to lift performance and deliver safer, more resilient operations.