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Intelligent light: the fusion of AI and lasers

Intelligent light: the fusion of AI and lasers
Intelligent light: the fusion of AI and lasers
Whilst femtosecond lasers allow precise micro-scale fabrication, the nonlinear laser-material interaction makes parameter optimisation challenging and the process highly sensitive to experimental fluctuations. This talk will explore how deep learning can predict machining outcomes, optimise parameters, and identify and correct errors in real-time, hence enhancing accuracy and efficiency in manufacturing.
Mills, Ben
05f1886e-96ef-420f-b856-4115f4ab36d0
Grant-Jacob, James A.
c5d144d8-3c43-4195-8e80-edd96bfda91b
Xie, Yunhui
c30c579e-365e-4b11-b50c-89f12a7ca807
Chernikov, Fedor
a5a56a14-d8cf-4a11-8946-dbb145dbda91
Liu, Yuchen
1efd4b12-3f11-4eb1-abea-0f5b40a1a9f1
Zervas, Michalis
1840a474-dd50-4a55-ab74-6f086aa3f701
Mills, Ben
05f1886e-96ef-420f-b856-4115f4ab36d0
Grant-Jacob, James A.
c5d144d8-3c43-4195-8e80-edd96bfda91b
Xie, Yunhui
c30c579e-365e-4b11-b50c-89f12a7ca807
Chernikov, Fedor
a5a56a14-d8cf-4a11-8946-dbb145dbda91
Liu, Yuchen
1efd4b12-3f11-4eb1-abea-0f5b40a1a9f1
Zervas, Michalis
1840a474-dd50-4a55-ab74-6f086aa3f701

Mills, Ben, Grant-Jacob, James A., Xie, Yunhui, Chernikov, Fedor, Liu, Yuchen and Zervas, Michalis (2024) Intelligent light: the fusion of AI and lasers. Laser Matters, Manufacturing Technology Centre, Coventry, United Kingdom. (In Press)

Record type: Conference or Workshop Item (Other)

Abstract

Whilst femtosecond lasers allow precise micro-scale fabrication, the nonlinear laser-material interaction makes parameter optimisation challenging and the process highly sensitive to experimental fluctuations. This talk will explore how deep learning can predict machining outcomes, optimise parameters, and identify and correct errors in real-time, hence enhancing accuracy and efficiency in manufacturing.

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More information

Accepted/In Press date: 6 November 2024
Venue - Dates: Laser Matters, Manufacturing Technology Centre, Coventry, United Kingdom, 2024-11-06

Identifiers

Local EPrints ID: 509443
URI: http://eprints.soton.ac.uk/id/eprint/509443
PURE UUID: 5e641de3-665c-4a4e-bc8e-f10b74d0e9ac
ORCID for Ben Mills: ORCID iD orcid.org/0000-0002-1784-1012
ORCID for James A. Grant-Jacob: ORCID iD orcid.org/0000-0002-4270-4247
ORCID for Yunhui Xie: ORCID iD orcid.org/0000-0002-8841-7235
ORCID for Yuchen Liu: ORCID iD orcid.org/0009-0008-3636-1779
ORCID for Michalis Zervas: ORCID iD orcid.org/0000-0002-0651-4059

Catalogue record

Date deposited: 23 Feb 2026 17:46
Last modified: 24 Feb 2026 03:10

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Contributors

Author: Ben Mills ORCID iD
Author: James A. Grant-Jacob ORCID iD
Author: Yunhui Xie ORCID iD
Author: Fedor Chernikov
Author: Yuchen Liu ORCID iD
Author: Michalis Zervas ORCID iD

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