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8th Machine Learning and AI in Bio(Chemical) Engineering Conference

01-02 July 2025
In person-only event
 
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Machine Learning and AI in Bio(Chemical) Engineering Conference series is co-organised by researchers linked with the Innovation Centre in Digital Molecular Technologies (iDMT), at the University of Cambridge. This series of conferences grew from two collaborative research projects on robotics and automation in chemical development (Glasgow, Leeds, Cambridge, UCL and Southampton). We continue to engage with the growing academic community in digital chemistry, chemical engineering and biochemical engineering, to design each iteration of the conference. 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.

The Conference

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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01 July 2025 (Tuesday), Day One

10:00 – 11:00    Welcome and refreshments

11:00 – 12:00    Keynote Speaker 1

12:00 – 12:25    Invited Speaker 1

12:25 – 12:50    Invited Speaker 2

12:50 – 14:00    Lunch

14:00 – 14:25    Oral Presentation 1

14:25 – 14:50    Oral Presentation 2

14:50 – 15:15    Oral Presentation 3

15:15 – 15:30    Break (Refreshments, Coffee and Tea)

15:30 – 16:00    Oral Presentation 4 (CINEMA)

16:00 – 16:25    Oral Presentation 5 (CINEMA)

16:50 – 17:15    Oral Presentation 6 (CINEMA)

17:15 – 19:00    Networking and Dinner

19:00                 End of day 1

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02 July 2025 (Wednesday), Day Two

09:00 – 09:15    Coffee reception

09:15 – 10:10    Keynote Speaker 2

10:10 – 10:35    Invited Speaker 3

10:35 – 11:00    Invited Speaker 4

11:00 – 12:45    Poster Session + Break (Refreshments, Coffee and Tea)

12:45 – 14:00    Lunch

14:00 – 14:25    Oral Presentation 7

14:25 – 14:50    Oral Presentation 8

14:50 – 15:15    Oral Presentation 9

15:15 – 15:40    Oral Presentation 10

TBC   Workshop (Accelerated Materials)

TBC    Closing Remarks & RSC Prize Presentation

TBC                 End of day 2

Speakers

Speakers

Keynote Speakers

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Professor Kim E. Jelfs
Imperial College London
Remembering the lab in computational molecular materials discovery

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Professor Garrett M. Morris
University of Oxford
Title TBC

Invited Speakers

Professor José Miguel Hernández Lobato

(University of Cambridge)

Deep generative models for molecule simulation

Professor Federico Galvanin

(University College London)

Autonomous platforms for model identification: The role of optimal experimental design

Professor Nicholas Ballard

(The University of the Basque Country)

Machine learning for polymer reaction engineering

Dr. Dasha Semochkina

(University of Southampton)

AI-powered bayesian framework for chemical kinetics: Towards efficient experimental design

Special Session

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ML/AI for Polymer Synthesis and Discovery

CINEMA brings together academic partners—the University of the Basque Country (UPV/EHU), Ghent University, RWTH Aachen, the Basque Center for Applied Mathematics, and the University of Cambridge—and industry leaders including Covestro, Arkema, Synthomer, and BASF. The initiative aims to develop machine learning-based methods for designing and controlling emulsion polymerization products and processes, combining cutting-edge machine learning techniques with fundamental scientific expertise.

Workshop

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Making it Modular: Scalable Automation Strategies for Modern R&D

Fully automated and autonomous laboratories are the future of chemical R&D. However, modern laboratories struggle to implement new technologies in AI and robotics fue to constraints in expertise, expense and time. In this workshop, founder and CEO of Accelerated Materials, Nicholas Jose, will cover current opportunites and challenges in autonomous R&D, and introduce modular design methodologies for creating automated yet versatile workflows. Participants will be lead through real world case studies in materials synthesis, formulation and more using AMLearn, the company's application for AI and Machine Learning integration.

Abstract Submission

The 8th International Conference on Machine Learning (ML) and AI in (bio)Chemical Engineering will take place on 01-02 July 2025. 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

  • Experimental case studies using ML

  • Method development, particularly those that simplify user experience

  • Benchmarking of ML and AI methods

  • AI for polymer development and property predictions

  • Machine learning in life cycle analysis and process intensification

  • Coupling AI with high-throughput experimentation or robotic platforms

  • Synergies between ML and quantum computing for chemical property predictions

 

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 16 May 2025.

Sponsors

Sponsors

Registration

Registration

01-02 July 2025
Hosted by the University of Cambridge
 

Fees include access to the event, refreshments for both days and conference networking dinner in the evening of Day 1.

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Early bird rate (£85) will finish on Friday May 16th and increase to the full rate (£105) thereafter.

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Contact

Department of Chemical Engineering and Biotechnology

Philippa Fawcett Drive 

Cambridge CB3 0AS 

United Kingdom

mab@ceb.cam.ac.uk

© 2025 by MAB

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