Research project

Lasers that Learn

Research groups:

Vision, Learning and Control

Nanophotonics Group
Lead researchers:

Dr Ben Mills
Other researchers:

Professor Robert Eason,

Professor Mahesan Niranjan,

Dr Matthew Praeger
Research funder:

EPSRC
Status:

Not active

Staff

Lead researchers

Dr Ben Mills

Principal Research Fellow

Connect with Ben

Email: [email protected]

Other researchers

Professor Robert Eason

Connect with Robert

Email: [email protected]

Professor Mahesan Niranjan

ISIS Chair

Connect with Mahesan

Email: [email protected]

Dr Matthew Praeger

Senior Research Fellow

Connect with Matthew

Email: [email protected]

Collaborating research institutes, centres and groups

Nanophotonics Group

We perform fundamental optical physics and materials research. This is critical for the discovery and development of new and improved optoelectronic technologies.

Vision, Learning and Control

Our work covers a range of technological areas from control, to machine learning and computer vision.

Research outputs

Predictive visualisation of fibre laser machining via deep learning

Alexander Courtier, Michael David Tom McDonnell, Matthew Praeger, James Grant-Jacob, Christophe A. Codemard, Benjamin Mills & Michael N. Zervas, 2021

DOI: 10.1109/CLEO/Europe-EQEC52157.2021.9542389

Type: conference

Playing optical tweezers with deep reinforcement learning: in virtual, physical and augmented environments

Matthew Praeger, Yunhui Xie, James Grant-Jacob, R.W. Eason & Benjamin Mills, 2021, Machine Learning: Science and Technology, 2(3)

DOI: 10.1088/2632-2153/abf0f6

Type: article

In-flight sensing of pollen grains via laser scattering and deep learning

James Grant-Jacob, Matthew Praeger, R.W. Eason & Benjamin Mills, 2021, Engineering Research Express, 3(2)

DOI: 10.1088/2631-8695/abfdf8

Type: article

Machine learning for multi-dimensional optimisation and predictive visualisation of laser machining

Michael, David Tom McDonnell, James Grant-Jacob, Benjamin Mills, R.W. Eason, Matthew Praeger, Dimitris Karnakis, Daniel Arnaldo & Etienne Pelletier, 2021, Journal of Intelligent Manufacturing, 32(5), 1471–1483

DOI: 10.1007/s10845-020-01717-4

Type: article

Semantic segmentation of pollen grain images generated from scattering patterns via deep learning

James Grant-Jacob, Matthew Praeger, R.W. Eason & Benjamin Mills, 2021, Journal of Physics Communications, 5(5)

DOI: 10.1088/2399-6528/ac016a

Type: article