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AI3SD Video: Applying Machine Learning to Structured Time-course sensor data

AI3SD Video: Applying Machine Learning to Structured Time-course sensor data
AI3SD Video: Applying Machine Learning to Structured Time-course sensor data
This talk forms part of the ML4MC (Machine Learning for Materials and Chemicals Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Directed Assembly Network. This series ran over summer 2021 and covers topics that encompass our overlapping Network interests of AI, Machine Learning, Artificial Photosynthesis, Biomimetic Materials, Crystal Design & Engineering, Materials, Molecules, Photochemistry, Photocatalysis and Supramolecular Chemistry. This video was the third talk in the ML4MC series and formed part of the session "Research Talks".
AI3SD Event, Directed Assembly, Materials, Chemicals, Machine Learning, Summer School, Training
Pattison, David
adc1ee82-2682-421b-a1b5-26ba69d98b91
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84
Pattison, David
adc1ee82-2682-421b-a1b5-26ba69d98b91
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84

Pattison, David (2021) AI3SD Video: Applying Machine Learning to Structured Time-course sensor data. Kanza, Samantha, Frey, Jeremy G. and Hooper, Victoria (eds.) Machine Learning for Materials & Chemicals Seminar Series 2021, , Southampton, United Kingdom. 06 Jul - 24 Aug 2021. (doi:10.5258/SOTON/P0130).

Record type: Conference or Workshop Item (Other)

Abstract

This talk forms part of the ML4MC (Machine Learning for Materials and Chemicals Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Directed Assembly Network. This series ran over summer 2021 and covers topics that encompass our overlapping Network interests of AI, Machine Learning, Artificial Photosynthesis, Biomimetic Materials, Crystal Design & Engineering, Materials, Molecules, Photochemistry, Photocatalysis and Supramolecular Chemistry. This video was the third talk in the ML4MC series and formed part of the session "Research Talks".

Video
Ml4MC-DavidPattison-200721 - Version of Record
Available under License Creative Commons Attribution.
Download (705MB)

More information

Published date: 20 July 2021
Additional Information: Dr David Pattison, Data Science Manager at DeepMatter. David has over a decade of experience in data science, AI and machine learning across a variety of data-intensive industries (renewables, nuclear, insurance and chemistry). He leads the development of data strategy, modelling and analytics for DigitalGlassware and the wider DeepMatter product base to bring value to chemists and chemical companies.
Venue - Dates: Machine Learning for Materials & Chemicals Seminar Series 2021, , Southampton, United Kingdom, 2021-07-06 - 2021-08-24
Keywords: AI3SD Event, Directed Assembly, Materials, Chemicals, Machine Learning, Summer School, Training

Identifiers

Local EPrints ID: 450667
URI: http://eprints.soton.ac.uk/id/eprint/450667
PURE UUID: d4f8670b-0aec-47c9-b363-14059e2c564a
ORCID for Samantha Kanza: ORCID iD orcid.org/0000-0002-4831-9489
ORCID for Jeremy G. Frey: ORCID iD orcid.org/0000-0003-0842-4302

Catalogue record

Date deposited: 05 Aug 2021 16:34
Last modified: 24 Aug 2021 01:55

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Contributors

Author: David Pattison
Editor: Samantha Kanza ORCID iD
Editor: Jeremy G. Frey ORCID iD
Editor: Victoria Hooper

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