7th Machine Learning and AI in Bio(Chemical) Engineering Conference
02-03 July 2024
In person-only event
Machine Learning and AI in Bio(Chemical) Engineering Conference series is co-organised by research groups of the Universities of Cambridge, Leeds, Glasgow, Southampton, and University College London. This series of conferences grew from two collaborative research projects on robotics and automation in chemical development. The conference will feature keynote and invited lectures from global champions of research in ML/AI in chemistry/(bio)chemical engineering, and regular lectures selected from the community submissions.
Conference Agenda
The event will be held at the Department of Chemical Engineering and Biotechnology,
Philippa Fawcett Dr, Cambridge CB3 0AS
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July 02th, Day one
10:00 – 11:00 Welcome and refreshments
11:00 – 12:00 Keynote Speaker #1
12:00 – 12:25 Oral Presentation #1
12:25 – 12:50 Oral Presentation #2
12:50 – 14:00 Lunch
14:00 – 14:35 Invited Talk #1
14:35 – 15:00 Oral Presentation #3
15:00 – 15:25 Oral Presentation #4
15:25 – 15:35 Break
15:35 – 16:10 Invited Talk #2
16:10 – 16:35 Oral Presentation #5
16:35 – 17:00 Oral Presentation #6
17:00 – 19:00 Networking and dinner
19:00 End of day 1
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July 03th, Day two
09:00 – 09:15 Coffee reception
09:15 – 09:40 Oral Presentation #7
09:40 – 10:05 Oral Presentation #8
10:05 – 11:50 Poster Session
11:50 – 12:25 Invited Talk #3
12:25 – 12:45 Oral Presentation #9
12:45 – 14:00 Lunch
14:00 – 14:35 Invited Talk #4
14:35 – 15:00 Oral Presentation #10
15:00 – 15:15 Break
15:15 – 16:15 Keynote Speaker #2
16:15 – 17:00 Closing Remarks & Prizes
17:00 End of day 2
Speakers
Confirmed speakers
Keynote speaker for 2024 edition
Andreas Bender
University of Cambridge, UBB Cluj, UMF Cluj, and Pangea Bio
Workshop
No-code Machine Learning in Chemistry: ReactWise
Alexander Pomberger & Daniel Wigh
The 7th International Conference on Machine Learning and AI in (bio)Chemical Engineering will take place on July 02-03 2024. We are requesting abstracts for posters and talks related to this theme. Potential topics/submissions include but are not limited to:
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Software implementations of key methods
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Experimental case studies using ML
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Method development, particularly those that simplify user experience
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Benchmarking of ML methods
Abstracts may be up to 400 words and optionally include explanatory figures. We emphasise that abstracts should include sufficient introduction for newcomers.
The deadline for submissions is 5 May 2024.
Recordings from last year are available!
Sponsors
