Events

 

In March 2024, we held a state of the nation event to discuss the state of data analytics in the UK and identify bottlenecks that is holding back the UK analytical sciences. As part of our effort to inspire the community towards good practice and showcase exemplar research in the UK, we are organising a series of free webinars events this year. 

 

With this in mind we are delighted to invite you to our first webinar in the Data Analytics series which is taking place on March 20, 2025. The event will include a 30 minute presentation followed by 30 minutes panel discussion.

 

 

Speaker: Kate Kemsley, Professor of AI in Chemistry School of Chemistry, Pharmacy & Pharmacology, University of East Anglia Lead, UEA Food Authenticity Centre of Expertise & Scientific Director, Mestrelab Research SL.

 

Kate’s early academic career at the UK's Institute of Food Research focused on infrared sensor design. Her PhD research, on chemometric analysis of the large datasets produced by infrared spectroscopy, led to a wider interest in the emerging disciplines of computational statistics and machine learning. Since then, she has published widely on the analysis of large ‘chemical profile’ datasets (FTIR, NMR, Raman) as well as image and time domain signals.  Key areas of application have been natural product integrity issues, and plant and human metabolomics studies. She leads on the Centre of Expertise in Food Authenticity at the University of East Anglia (UEA), and since 2023 has been a Scientific Director at Mestrelab Research SL, a leading producer of scientific software for analytical instrumentation.

 

Profile pages: Kate Kemsley - University of East Anglia

 

 

 

Advances in AI are transforming the way large analytical datasets are processed and interpreted. This talk will focus on recent developments in predictive modelling at the molecular sub-structure level, in particular its role in improving the assignment and verification of NMR spectra.  Drawing on real-world examples from the food and drugs sectors, I will also touch on the use of machine learning as well as traditional chemometric approaches for treating classification problems, contrasting their strengths and limitations and how these might impact on decision-making in analytical chemistry.

 

Your expertise in this field will be highly valued and a great addition to the webinar. We ask you please to confirm your attendance by registering here

 

 

We look forward to welcoming you on the day,

CAMS Secretariat