Overview

This is the third webinar in a collaborative series by the Food & Drink and Process Management & Control Special Interest Groups.

Effective AI solutions require the combination of different digital technologies. The Leeds University Food AI Lab has world leading expertise in Sensing, Machine learning and Optimisation within food systems. They focus on addressing barriers to industry adoption including cost, trust and usability.

This webinar will give an overview of their research on the sensing, machine learning and optimisation and then will dive into their work on using acoustic (immersion/contact/non-contact ultrasound) and optical (NIR, hyperspectral, colour imaging) sensing with energy/water monitoring, deployed in labs and industrial settings - e.g. for allergen detection - as well as a case study on sustainable brewing through beer fermentation end point detection by combining Ultrasonic Sensing with Transfer and Federated Learning.

Speaker

Nik Watson, Professor of Artificial Intelligence in Food, Leeds University Food AI Laboratory

Nik’s research focuses on developing digital technologies and solutions to address critical challenges in environmental sustainability, food safety, resilience, and health across food production systems. His work emphasizes the integration of low-cost sensors (e.g., acoustic and optical) with advanced machine learning methods to enable real-time monitoring of material properties and the optimisation of food production processes. Currently, his research is strongly aligned with advancing the circular bioeconomy and exploring innovations in alternative proteins. With expertise spanning all technology readiness levels, Nik has a proven track record of collaborating with industry partners across diverse food sectors and business scales—from micro-SMEs to multinational corporations.

His ability to bridge academic research with industrial applications ensures that his work delivers tangible, real-world impact. Nik holds an MEng in Mechanical Engineering from the University of Hull (2006) and a PhD in Chemical Engineering from the University of Leeds (2010). Following his doctoral studies, he served as a Post-Doctoral Research Assistant in the Food Physics Lab at the University of Leeds from 2010 to 2014. He then advanced to roles as an Assistant/Associate Professor of Chemical Engineering at the University of Nottingham. In 2023, Nik returned to the University of Leeds to take up his current professorial appointment, where he continues to drive innovation at the intersection of artificial intelligence and food.

Tom Hazlehurst, Research Fellow in Artificial Intelligence for Sustainable Food, Leeds University Food AI Laboratory

Tom is a Research and Innovation Fellow at the University of Leeds, working within the School of Food Science and Nutrition. Their research focuses on applying artificial intelligence and machine learning to tackle challenges in food security and alternative protein development, particularly through the NAPIC (National Alternative Protein Innovation Centre) project. With a background in applied mathematics and extensive experience in both academia and with industrial partners, Tom has contributed to cross-sector collaborations involving machine learning for process control, particle analysis, and materials discovery. Their work bridges data science and food systems to support sustainable and scalable innovation. Tom holds a PhD in Applied Mathematics and an MMath, BSc from the University of Leeds.

The material presented has not been peer-reviewed. Any opinions are the presenter’s own and do not necessarily represent those of IChemE, the Process Management & Control or the Food & Drink Special Interest Groups. The information is given in good faith but without any liability on the part of IChemE.

Time

09:00–10:00 BST.

Software

The presentation will be delivered via Microsoft Teams. We recommend downloading the app from the Microsoft website, rather than using the web portal.