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Prof Andrew French

Professor, Faculty of Science

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Biography

I am interested in Artifical Intelligence (AI) research, particularly related to understanding images. Building an understanding of AI within other disciplines, especially within the biological sciences, has been a focus in recent years, and is increasingly important as AI tools become more powerful.

Research interests include:

· Image analysis of plants and other complex structures

· Developing novel AI software tools to aid biologists

· Deep machine learning approaches

· Artificial intelligence for computer vision

· Automating image capture approaches (e.g. with robotics)

Expertise Summary

Image analysis and computer vision

Biological image analysis

Artificial intelligence methods for computer vision

Deep machine learning

High-throughput plant phenotyping

Experience with a variety of dataset modalities (colour, 3D volumetric, x-ray. MRI, confocal, LSFM etc.)

Data science training provision (via free courses and consultancy)

Teaching Summary

I mainly teach Computer Vision and Schools Experience in Computer Science, and Computer Modelling in Science (Introduction and Applications) in Biosciences. I do supervise final year projects: if you… read more

Research Summary

My research involves developing novel computer science approaches to solve imaging challenges, particularly in bioscience applications. This includes machine learning approaches as well as image… read more

Selected Publications

I have offices on Sutton Bonington and Jubilee campuses.

On SB, you can find me in Plant Sciences, C08a. My office in Computer Science is B80. You are welcome to try dropping by, but it is best to email me first for an appointment.

I mainly teach Computer Vision and Schools Experience in Computer Science, and Computer Modelling in Science (Introduction and Applications) in Biosciences. I do supervise final year projects: if you are interested in image analysis, do email me with project ideas.

Current Research

My research involves developing novel computer science approaches to solve imaging challenges, particularly in bioscience applications. This includes machine learning approaches as well as image analysis development.

Research interests include:

· Image analysis of plants and other complex structures

· Developing novel software tools to aid biologists and mathematical modellers

· Deep machine learning approaches

· Automating image capture approaches (e.g. with robotics)

Past Research

Tracking algorithm development: how to track objects in video sequences.

Future Research

Developing deep learning approaches to image analysis.

Phenotyping - automating the characterization of plants using imaging, robotics and automation software to speed up the number of plants we can measure in an experiment.

Segmentation methods, including superpixel approaches.

Hyperspectral imaging

Generating 3D models

MRI segmentation and interpretation.

World-class research at the University of Nottingham

University Park
Nottingham
NG7 2RD
+44 (0) 115 951 5151
research@nottingham.ac.uk
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