Machine Learning in Disordered Photonics

Project description

Learning more about exotic light-scattering materials helps us to harness them

Like a bunch of pinballs reverberating around a pinball machine and bouncing off everything including each other, photons entering disordered materials are scattered several times before leaving the materials in random directions. The "dance" can continue, with the random rays interfering once again with each other. This amazing light show, if harnessed, can be used to develop innovative photonics devices. Until now, characterisation enabling the rational prediction of the properties of disordered materials and their subsequent design was an important roadblock. The EU-funded MALDIP project plans to apply machine-learning techniques and numerical simulations to get to the bottom of things.

Fields of science

• natural sciences › mathematics › applied mathematics › statistics and probability
• natural sciences › computer and information sciences › artificial intelligence › machine learning
• engineering and technology › nanotechnology › nanophotonics
• natural sciences › mathematics › applied mathematics › numerical analysis

Programme(s)

• H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme
• H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility

Topic(s)

• MSCA-IF-2019 - Individual Fellowships

Call for proposal

H2020-MSCA-IF-2019

See other projects for this call

Funding Scheme

MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)

Coordinator

THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE

Net EU contribution

€ 212 933,76

Address

Trinity Lane The Old Schools
CB2 1TN Cambridge
United Kingdom

Region

East of England › East Anglia › Cambridgeshire CC

Activity type

Higher or Secondary Education Establishments

Links

Other funding

€ 0,00