Alex Bowler
- Position: Research Assistant
- Areas of expertise: Ultrasonic sensors; Machine learning; Transfer learning; Domain adaptation; Near-infrared spectroscopy; Process monitoring
- Email: A.L.Bowler@leeds.ac.uk
- Location: EC Stoner Building
- Website: LinkedIn
Profile
I completed my MEng in 2018 and recently defended my PhD thesis in 2022, both in Chemical Engineering at the University of Nottingham. My PhD thesis was titled "Ultrasonic measurements and machine learning methods to monitor industrial processes". The focus of my thesis was on developing a machine learning pipeline as well as transfer learning and domain adaptation methods for process monitoring using ultrasonic sensors.
I joined the University of Leeds in 2023 as a research assistant on the EATS (Enhancing Agri-Food Transparent Sustainability) EPSRC funded project. As part of this project, I am investigating open-source carbon footprint calculations, Bayesian optimisation of brewery processes, and real-time process optimisation using sensor measurements. Additionally, I have also worked on other areas of research such as near-infrared spectroscopy for allergen classification in food powders, commodity price forecasting for techno-economic analyses, and domain adaptation methods for colour sensors.
<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="https://environment.leeds.ac.uk/dir/research-projects">research projects</a> allows you to view and search the full list of projects in the faculty.</p>Qualifications
- MEng Chemical Engineering (University of Nottingham)
Research groups and institutes
- Food Colloids and Processing