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Energy

Interdisciplinary Research Centre
 
Date: 
Tuesday, 2 July, 2024 - 10:00 to Wednesday, 3 July, 2024 - 16:30
Event location: 
Department of Chemical Engineering and Biotechnology, Philippa Fawcett Dr, Cambridge CB3 0AS

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.

Full full programme and registration: https://www.mabc-cambridge.ai/

July 02th, Day one

10:00 – 11:00    Welcome and refreshments

11:00 – 12:00    Andreas Bender (Keynote) - Using Chemical and Biological Data for Drug Discovery – Methods, Applications, and Pitfalls

12:00 – 12:25    Jiayun Pang - Enhancing Drug Discovery with Contrastive-Finetuned Sentence-Transformers 

12:25 – 12:50    Wenyao Lyu - DoE-SINDy: an automated framework for model generation and selection in kinetic studies 

12:50 – 14:00    Lunch

14:00 – 14:35    Adam Clayton - Bayesian Self-Optimisation for Multistep Flow Processes and Mixed Variable Reactions 

14:35 – 15:00    Johannes Seiffarth - Beyond observation in microbial live-cell imaging: Exerting control on microbial populations using real-time AI image analysis and response triggering

15:00 – 15:25    Jiaru Bai - twa: A dynamic knowledge graph Python package for interoperable chemistry 

15:25 – 15:35    Break

15:45 – 16:10    Maximilian Bloor - PC-Gym: Reinforcement Learning Environments for Process Control 

16:10 – 16:35    Arun Pankajakshan -  Bayesian Classification with Active Learning for Closed-loop Identification of Feasible Operating Region in Continuous Flow Crystallization 

16:35 – 17:00    Henrique Marcon -  AI-driven site selectivity in halogenation chemistry 

17:00 – 19:00    Networking and dinner

19:00                 End of day 1

July 03th, Day two

09:00 – 09:15    Coffee reception

09:15 – 09:50    Michele Assante - Automation of ab-initio calculations for data-driven reaction models: prediction of Nickel-catalyzed metallaphotoredox sp2-sp3 cross-coupling reactions

09:50 – 10:15    Hugo Bellamy - Incorporating uncertainty information into drug design problems 

10:15 – 11:15    Fernanda Duarte (Keynote) - Bridging the Gap: Enhancing Retrosynthesis Prediction for Heterocycle compounds

11:15 – 12:50   Poster Session

12:50 – 14:00    Lunch

14:00 – 14:25    Thomas Andrews - A Self-Optimizing Platform for Continuous Flow Transfer Hydrogenations Using Catalytic Static Mixer Technology 

14:25 – 15:15    Workshop - Reactwise (Henrique Marcon)

15:15 – 15:40    Emmanuel Agunloye - Application of Artificial Neural Networks Classifier for Rapid Identification of Chemical Reactor Models 

15:40 – 16:05   Aniket Chitre - Accelerating Liquid Formulations Design using Lab Automation and Machine Learning

16:05 – 16:35    Closing Remarks & Prizes 

16:35                  End of day 2