Join host Santi Dominguez in the latest MestreCast episode, "AI Modelling of molecular properties - the next frontier in chemical space" featuring Prof. Kate Kemsley, Mestrelab's Scientific Director with a rich background in physics and statistics. Together, they explore the integration of artificial intelligence in NMR spectroscopy, focusing on Kate's work with message passing neural networks for chemical shift prediction.
This concise yet insightful episode sheds light on the challenges of melding AI with analytical chemistry, the precision of new predictive methods, and the potential to transform data processing. Kate shares her journey from computational statistician to leading AI research at Mestrelab, aiming to revolutionize how chemists interact with spectroscopy data.
You can also tune in on Spotify, Apple Podcasts, iVoox to catch a glimpse of the future where AI empowers researchers and chemists with unprecedented accuracy and efficiency.
Would you like to try Mestrelab's ensemble NMR prediction software package? Click here if you're interested in running a 45-day trial of Mnova NMR Predict!
00:00:00 Intro
00:01:28 You joined Mestrelab in October as a scientific director – what attracted you to the role?
00:03:48 Your role is focused on the data processing side of things, tell me more about that?
00:04:55 What research are you currently working on?
00:06:29 Could you elaborate on how message passing neural networks work?
00:08:45 Who do you see this tool appealing to, who will be the end-users?
00:10:14 Have you encountered any challenges along the way?
00:11:40 Any other challenges?
00:12:28 Why is that important?
00:19:14 Can you share a bit about your professional journey leading up to this role?
00:20:30 What was the subject of your research there?
00:21:20 What drives your enthusiasm for data analytics
Guest Speaker
Prof. Kate KemsleySenior Scientific DirectorMestrelab Research
Guest Speaker
Senior Scientific DirectorCEOMestrelab Research