Professor Nicholas Watson

Professor Nicholas Watson


Nik is an  Engineer with a MEng in Mechanical Engineering (University of Hull, 2006) and PhD in Chemical Engineering (University of Leeds, 2010). From 2010 - 2014 Nik worked as a Post-Doctoral Research Assistant in the Food Physics Lab at the University of Leeds. During this time, he developed a number of acoustic sensing technologies for industry partners. In 2014 Nik was appointed as an Assistant Professor of Chemical Engineering at the University of Nottingham and was promoted to an Associate Professor in 2020. During his time at Nottingham, Nik focussed on combining in-process sensing (acoustic and optical) with machine learning for a variety of industrial applications and developed expertise in the broad area of Digital Manufacturing within the Food and Drink Sector. Nik Joined the University of Leeds in 2023 as a Professor of Artificial Intelligence in Food. During his career Nik has published over 70 articles and led projects funded by Innovate UK, EPSRC, STFC and the Royal Academy of Engineering.

Nik is an active member of the UK's Digital Manufacturing research community and currently a Co-Investigator on the EPSRC's Digital Manufacturing Network: Connected Everything. Nik regularly speaks at Industry events on the topic of Digital Manufacturing, Industry 4.0 and Artificial Intelligence within the food and drink sector with invited international talks including: The Food and Drug Administration's Applications of Artificial Intelligence in Food and Cosmetics Safety Colloquium (2020) and the Australian Institute of Food Science and Technology Virtual Convention (2020). Nik has extensive industry collaborative experience with manufacturers in the food and drink, pharmaceutical and FMCG sectors ranging from micro-SMEs to multinationals. He also works closely with digital technology providers and integrators. Nik was previously a member on the EPSRC's Early Career Forum in Manufacturing Research and is currently on the Food Standards Agency's Register of Experts.

Research interests

Nik's research is focussed on developing digital technologies and solutions to address environmental sustainability, food safety and health challenges in food production systems. His particular expertise lies within combining low costs sensors (e.g. acoustic and optical) with machine learning models to monitor and optimise production processes and predict food properties.

Nik's team has developed data-driven in-process sensing methods for a variety of applications including:

  • Food and drink fermentation
  • Inline food quality assessment (e.g. texture)
  • Clean-in-place 
  • Adulteration of food materials
  • Allergen detection in powdered foods
  • Dry matter and sugar content in root crops
  • Poultry inspection

He is currently interested in addressing the challenges of deploying digital technologies and solutions in the food sector with specific priorities including:

  • Multi-sensor data fusion to collect appropriate datasets to characterise complex, heterogeneous biological materials (foods!)
  • Minimising the data collection and labelling burden through transfer, federated, semi-supervised and active learning 
  • Model trust through explainable and interpretable models 
  • Human in the loop and hybrid modelling methods
<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="">research projects</a> allows you to view and search the full list of projects in the faculty.</p>


  • PhD (University of Leeds)
  • MEng (University of Hull)

Professional memberships

  • FHEA

Research groups and institutes

  • Food Colloids and Processing
<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="">research opportunities</a> allow you to search for projects and scholarships.</p>
    <li><a href="//">AI-Optimised Fermentation for Sustainable Protein Production from Food Side Streams</a></li> <li><a href="//,-wellbeing-and-technical-performance-using-artificial-intelligence">Designing chocolate products with enhanced health, wellbeing and technical performance using artificial intelligence</a></li>