Tuesday 2 July 2024 10:00am to Wednesday 3 July 2024 4:30pm
Department of Chemical Engineering and Biotechnology, Philippa Fawcett Dr, Cambridge CB3 0AS
About
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