The 3rd conference in the series of outreach events co-organised by research consortia of the EPSRC-funded projects "Combining Chemical Robotics and Statistical Methods to Discover Complex Functional Products" and "Cognitive Chemical Manufacturing" will take place online, hosted by the Department of Chemical Engineering and Biotechnology, University of Cambridge.
Talks will be recorded and shared in advance, with online discussion sessions held over video conferencing software on 8-9 July. There will also be online poster sessions scheduled across the two days.
Submit your poster
Poster presentations are welcome: to present a poster please submit your proposed title to Dr Danilo Russo. For ‘poster’ presentations, please prepare 4-slides and a 3-minute recording. We will need to upload these to be available to all participants by 1st of July.
There will be a £100 cash prize for best poster, sponsored by the Royal Society of Chemistry journal, Reaction Chemistry & Engineering.
To register interest for the conference, please send an email to Dr Danilo Russo.
Lectures confirmed
Antonio Del Rio Chanona “Merging Machine Learning and Real Time Optimisation”
Imperial College London
Thomas Savage and Dongda Zhang “Data-Driven Modelling and Optimisation Applied to LNG Refrigeration Cycles”
University of Manchester
Jose Miguel Hernandez Lobato "Weighted Retraining for Efficient Latent Space Optimization"
University of Cambridge
Alex Howarth, Kris Ermanis and Jonathan Goodman “DP4-AI and the automation of analytical chemistry”
University of Cambridge
Pietro Lio "Machine Learning for life sciences"
University of Cambridge
Gabor Csanyi “Machine Learning Molecular Forcefields”
University of Cambridge
Federico Galvanin “Machine learning-assisted experimental design techniques for kinetic model identification“
University College London
Artur Schweidtmann “Maximizing the acquisition function of Bayesian optimization to guaranteed global optimality”
RWTH Aachen
Liwei Cao, Danilo Russo, Alexei Lapkin “ML for Formulations Design”
University of Cambridge
Sebastian Ahnert “Discovering new materials by detecting modules in atomic networks”
University of Cambridge
Jan G. Rittig, Artur M. Schweidtmann, Andrea König, Manuel Dahmen, Martin Grohe, Alexander Mitsos “Deep End-To-End Learning on Molecular Graphs for Physico-Chemical Property Prediction using Graph Neural Networks”
RWTH Aachen
Panagiotis Petsagkourakis “Safe model-based design of experiments using Gausian processes”
University College London
Panagiotis Petsagkourakis "Constrained Reinforcement Learning for Process Optimization and Control under uncertainty"
University College London
Gregor Simm, Robert Pinsler and Jose Miguel Hernandez-Lobato "Reinforcement Learning for Molecular Design Guided by Quantum Mechanics"
University of Cambridge
Roohollah Hafizi, Olga Egorova, Graeme Day and Dave Woods "Multi-fidelity Statistical Machine Learning for Organic Molecular Crystal Structure Prediction"
University of Southampton
Kerry Gilmore “Predicting Glycosylation Stereoselectivity”
Max-Planck Institute of Colloids and Interfaces, Potsdam, Germany
EPSRC projects updates
Combining Chemical Robotics and Statistical Methods to Discover Complex Functional Products
Alexei Lapkin
Cognitive Chemical Manufacturing
Richard Bourne
