Professorial Lecture by Professor Melanie Po-Leen Ooi

Tue Mar 10 2026 at 05:30 pm to 06:30 pm UTC+13:00

Gallagher Academy of Performing Arts | Hamilton

The University of Waikato
Publisher/HostThe University of Waikato
Professorial Lecture by Professor Melanie Po-Leen Ooi
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Can AI control light to improve what it sees? Discover how frontend machine learning may lead to a physical AI vision-based measurement.
About this Event

'Next Generation Vision Measurement Systems' by Professor Melanie Po-Leen Ooi.

The journey from "what you see" (the physics of light) to "how you see" (the measurement process) and ultimately "how you decide" (data analysis and decision-making) is fraught with complexities. In vision systems, light is fundamentally an operational measurement whereby its meaning is determined by how the system operates, not just the underlying physics or the machine learning model applied afterward.

Currently, state-of-the-art machine learning algorithms function as passive, "backend" tools that analyse images only after they have been captured. This traditional approach forces a reliance on impossibly large training datasets to account for every real-world variable, creating an insurmountable bottleneck for real-world vision measurement systems in industries like manufacturing, smart agriculture, and environmental monitoring.

This Professorial Lecture provides an overview of the vision-based measurement and data analysis pipeline. It explores how light is controlled and captured, how systems are calibrated, and how the resulting data is reported. Most importantly, it questions whether the next generation of vision measurement systems can push machine learning to the "frontend" of the pipeline. By allowing AI to actively control the physical illumination source in a closed-loop, the system can physically tune its incoming images based on the rules it discovers during modelling. Through this approach, the AI can test its own decisions in real-time, for example, by adjusting light wavelengths to verify the presence of a specific material of defect, resulting in systems that may someday learn to see the unknown, and the unseen.


This 45-minute public lecture will be held at the at the University of Waikato in Hamilton, starting at 5.45pm. Ticket scanning and Opus Bar will be open from 5pm.

Free parking is available on campus via Gate 2B, Knighton Road, Hamilton from 4.30pm.

Please register your attendance by clicking on the 'select tickets' button above and bring your eticket, with you on the evening to be scanned.

If you would like to hear from us about future Public Lectures held at the University of Waikato, please join click to join our mailing list.



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earned her BEng (Hons), Master in Engineering Science (Research), and PhD from Monash University. She is currently a Professor in Mechatronics Engineering and Assistant Dean (Research) at the University of Waikato, having previously held leadership roles at Unitec Institute of Technology and Heriot-Watt University. Her research focuses on instrumentation, measurement, and computer vision systems for industrial monitoring, with a particular emphasis on semiconductor production, smart agriculture, and environmental sensing.

Her work has led to new testing standards adopted by global industry leaders such as Texas Instruments and Western Digital, and her uncertainty propagation frameworks are utilised in the South African National Accreditation System guidelines document TG-50-02.

Professor Ooi is a Fellow of the IET and U.K. Chartered Engineer, the Editor-in-Chief of the IEEE Instrumentation and Measurement Magazine, and recipient of several awards including the 2023 IEEE Internet Computing Best Paper Award from the IEEE Computer Society, the 2019 Rutherford Fellowship from the New Zealand Royal Society, the 2017 IET Mike Sargeant Medal from the IET U.K., and the 2014 IEEE Instrumentation and Measurement Society Outstanding Young Engineer of the Year from the IEEE Instrumentation & Measurement Society.


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Event Venue & Nearby Stays

Gallagher Academy of Performing Arts, The University of Waikato, Hamilton, New Zealand

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