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5th Machine Learning and AI in Bio(Chemical) Engineering Conference

Hosted by the University of Cambridge
 
27-28th June 2022
 

Event booklet available!

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.

 

The 2022 edition of the conference will be run as a hybrid event. The in-person attendance will be limited to 85 participants. The online event is unlimited; recordings of the sessions will be made available to the registered participants. A specific online poster and networking session will be run for the virtual participants.

Conference Agenda

June 27th, day one

10:00 - 11:00    Welcome and refreshments

11:00 - 12:00    Keynote 1 – Connor Coley - AI for chemical space navigation and synthesis

12:00 - 12:25    Adarsh Arun – Reaction impurity prediction using a data mining approach

12:25 - 12:50    A. Kondinski – Automated rational design via knowledge engineering

12:50 - 14:00    Lunch

14:00 - 14:35    Ruben Sanchez-Garcia - Compound availability and the numbers we care about in computationally-driven drug discovery

14:35 - 15:00    Harry Kay - Developing a novel soft-sensing framework for industrial data analysis and batch process monitoring

15:00 - 15:25    Calvin Tsay - SnAKe: Bayesian Optimization with Pathwise Exploration

15:25 - 15:35    Break

15:35 - 16:10    François-Xavier Felpin - Autonomous Flow reactors Associating In-line/Online Analyses and Feedback Algorithms

16:10 - 16:35    Ioana Gherman - Accelerating whole cell modelling with machine learning

16:35 - 17:00    Haiting Wang – A Hybrid Modelling Framework for Bioprocess

17:00 - 17:25    Pierre-Aurelien Gillot  - Systemic comparison of neural network architectures for protein expression prediction in bacteria

17:25 - 19:15    Networking and dinner

19:15                Day 1 end

 

June 28th, day two

09:00 - 09:15    Coffee reception

09:15 - 10:00    Workshop part 1 - Scaling up & scaling out compound generation and simulation with Grid.ai

10:00 - 10:15      Break

10:15 - 11:00    Workshop part 2

11:00 – 12:00   Poster Session

12:00 - 12:35    Carl Poelking - Strategies for bias compensation and synthetic control in AI-driven structure-based drug design

12:35 - 13:00    Miguel Angel de Carvalho Servia - Automated Kinetic rate equation discovery- A methodological framework

13:00 – 14:00    Lunch

14:00 - 15:00    Keynote 2 – Kerry Gilmore - Towards understanding and controlling mechanistically ambiguous transformations

15:00 - 15:25    Felix Strieth-Kalthoff - Closing the Loop in Materials Discovery: The Quest for Organic Lasers

15:25 – 15:45   Break

15:45 - 16:10    Venkat Kapil - The first-principles diagram of monolayer nanoconfined water

16:10 – 16:35    Abhishek Sharma - AI-EDISON: Autonomous Intelligent Exploration, DIScovery and Optimisation of Nanomaterials

16:35 - 17:00    Closing Remarks

17:00                End of day 2

 

​June 29th, day three

The iDMT event; separate registration is required. 

Information on the iDMT event is on the web page: https://www.idmt.online/digital-labs

 

Speakers

We are proud to bring inspirational speakers from across the globe

Confirmed speakers

Prof. Dr. Connor W. Coley (Massachusetts Institute of Technology - MIT)
  • "AI for chemical space navigation and synthesis"

Prof. Dr. Kerry Gilmore (University of Connecticut)
  • "Towards understanding and controlling mechanistically ambiguous transformations"

Prof. Dr. François-Xavier Felpin (University of Nantes)
  • "Autonomous flow reactors associating In-line/Online analyses and feedback algorithms"


Dr. Carl Poelking (Astex Pharmaceuticals)
  • "Strategies for bias compensation and synthetic control in AI-driven structure-based drug design"


Dr. Ruben Sanchez-Garcia (University of Oxford)
  •     "Compound availability and the numbers we care about in computationally-driven drug discovery"
Dr. Felix Strieth-Kalthoff (University of Toronto)
  • "Closing the Loop in Materials Discovery: The Quest for Organic Lasers"
Dr. Ross Johnstone (Research Engineer, SyntheticGestalt)
Robert Lee (Head of Solutions Architecture, Lightning AI)
  • Workshop on "Scaling up & scaling out compound generation and simulation with Grid.ai"
 
 

Sponsored by

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Early Career research talks
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Poster session

Registration

27-28th June 2022
 
Hosted by the University of Cambridge
 
 
 

Abstract Submission

The 5th International Conference on Machine Learning and AI in (bio)Chemical Engineering will take place on June 27-28, 2022 in Cambridge as a hybrid event. We are requesting abstracts for posters and talks related to this theme. Potential topics/submissions include but are not limited to:

  • Software implementations of key methods

  • Experimental case studies using ML

  • Method development, particularly those that simplify user experience

  • 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.