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Department of Chemical Engineering and Biotechnology

 

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

This event is sponsored by

 

Date: 
Wednesday, 8 July, 2020 - 11:00 to Thursday, 9 July, 2020 - 16:00
Contact name: 
Dr Danilo Russo
Contact email: 
Event location: 
Online