Webinar: AI-driven mineral analysis: Enhancing speed and accuracy by AZoNetwork Webinars

AI-driven mineral analysis: Enhancing speed and accuracy

About

AI is transforming various scientific fields, and mineralogy is no exception. By leveraging AI, you can analyze vast amounts of geological data faster and with greater precision than ever before. This innovative approach not only accelerates the identification and classification of minerals but also enhances predictive insights into mineral deposits.

Join us on this webinar to learn more about how these advancements are directly benefiting the mining industry.

With no coding experience, learn how AI-driven solutions can help you to:

> Automate repetitive tasks
> Refine data analysis processes
> Derive more accurate models from complex geological datasets

Who should attend this event?

This webinar is ideally suited for anyone working as a:

> Geologist
> Mineralogist
> Metallurgist
> Process Engineer
> Exploration Geologist
> Improvement Supervisor

Presenters

Dr. Rich Taylor

Geoscience Applications Development, Raw Materials Business Sector | ZEISS Research Microscopy Solutions

Dr. Rich Taylor completed a PhD in Experimental Petrology at the University of Edinburgh in 2009, before moving to Curtin University in Western Australia as a SIMS laboratory specialist. He subsequently held research positions in the School of Earth and Planetary Sciences at Curtin studying geochemistry and geochronology, specialising in imaging and microanalysis. In 2017 he moved to the University of Cambridge to study magnetic inclusions in Earth's oldest materials using novel microscopy techniques. In 2019 Rich moved to Zeiss based in Cambourne, UK to take on the global Geosciences Applications Development role.

Molly McQuilken, PhD

Business Development Software Solutions | ZEISS

Molly McQuilken is a Business Development Manager for ZEISS software solutions. She has worked for ZEISS for 7-years specializing in finding customers the right products to fit their image analysis needs. Prior to working with ZEISS, Molly completed her PhD at Dartmouth where she supported the development of an open-source image analysis toolkit. This image analysis background allows her to intuitively understand your imaging challenges and ensure you have a specified software solution which matches your needs and will support your research as it grows long-term.

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