Daniel Gudgeon is the Advanced Process Control (APC) Manager at Woodgrove Technologies. Based in the Greater Toronto Area, Daniel He leads the development and rollout of control solutions that stabilize circuits, reduce operator load, and unlock performance across crushing, grinding, flotation, POX/autoclave, thickening, and CIL. A Queen’s University graduate with over a decade of experience in operations optimization, he specializes in Advanced Process Control and process optimization. His work focuses on designing and deploying robust, operator-friendly APC—feed-forward, fuzzy logic, and constraint handling—that improves stability, reliability, and overall plant performance.

Maxwell Norris is a seasoned Extractive Metallurgist with over 12 years of expertise in Operational Safety, Production, Laboratory Management, and Project Management. Currently serving as Principal Metallurgist at Harmony Gold Mining, Maxwell leads in designing metallurgical testwork plans and collaborates on Model Predictive Control development. Maxwell's diverse experience includes key roles at Ok Tedi Mining Limited and Newcrest Mining Limited's Lihir Gold Mine, showcasing leadership in safety compliance, process optimization, and project management. His technical proficiency extends to various software tools, and he is currently pursuing additional qualifications in economics and safety management. Mr Maxwell Norris has been working with Rockwell Automation on Pavilion8 MPC projects, including the topic of today’s discussion, the optimisation of the Harmony Gold, Hidden Valley, processing plant

Warwick Smith is a Principal with Hatch in the digital business practice with 2026 years’ experience in mining. He has broad operational and technical experience in a range of minerals processing plants and smelters, including 10 years at Mount Isa Mines where he was the Operations Manager for the Zinc Lead Concentrate and Lead Smelter. Warwick has extensive experience in the empirical modelling of flotation processes utilising live sensor data for near real-time prediction. For the past 6 years, Warwick has worked in the area of advanced decision support systems at various Australian and international sites, either leading design and implementation projects or providing independent review of existing systems. He specializes in the application of modern machine learning to process optimisation and decision automation for operators.

Doctor of Industrial Chemistry and Reaction Engineering with over 15 years of experience in process modeling and simulation. Possessing a robust academic background, I have worked across various fields, including electrochemical reactor design, oil refining, renewable fuels production, and metallurgy. With more than 10 years of experience in Research and Development (R&D), successfully managing large-scale modeling projects and collaborating with diverse stakeholders. My role often involves coordinating with cross-functional teams, including engineers, operators and business leaders, to drive innovative solutions leading to optimized processes. Currently, I focus on applying machine learning and artificial intelligence to process modeling and optimization. This involves integrating chemical engineering expertise with advanced modeling techniques. My primary areas of interest include first-principle's modelling, deep reinforcement learning, and scientific machine learning. I am dedicated to leveraging digital solutions to drive process optimization and create significant value, always striving to push the boundaries of innovation in the field.