Machine Learning and Computational Intelligence

We work on the development and application of machine learning and computational intelligence methods to address biomedical and engineering problems characterised by large volumes of complex data.

Large volumes of complex data is often a key feature of biomedical and engineering problems, including for example the understanding of cell behaviour and fate using high resolution microscopy data, the analysis of structural and functional integrity of concrete structures using non-destructive imaging data, the assessment of the medication state of Parkinson’s disease patients using high resolution multi-accelerometer data, or prediction of deformation of materials used in high-pressure industrial processes.

We use computational intelligence and machine learning techniques to address such problems. We are interested in applications of neural networks, support vector machines, reservoir computing, evolutionary optimisation, pattern recognition methods and other techniques to develop practical and validated solutions to hard biomedical and engineering problems. We also work on the theoretical development of machine learning techniques, for example on novel methods for syntactic pattern recognition, Bayesian interpretation of swarm optimisation, and new approaches to approximation of functions defined on high-dimensional spaces.

This figure is about automated recognition of cells using confocal imaging data.
This figure is about automated recognition of cells using confocal imaging data.

We expect that our work will have significant impact in many areas. For example, our automated analysis of ageing of construction materials is expected to lead to much improved infrastructural building maintenance; our work on automated analysis of biomedical imaging data can speed up significantly the progress of medical research requiring the understanding of large volumes of images; and our work on syntactic image analysis may lead to improved novel ways of representing and storing images.

Research Lead

Members

  • Machine learning analysis of industrial data, KTP project in collaboration with XACT PCB Ltd, 2013-2015, GBP 153k – Prof Peter Andras (PI; Newcastle University).
  • Development of e-Science platform technology, EPSRC, 2006-2009, GBP 208k – Prof Peter Andras (CI; Newcastle University).
  • Data mining of eBay data, NStar proof-of-concept funding, 2006, GBP 90k – Prof Peter Andras (PI; Newcastle University).
  • Computational analysis of communications about chemical safety, DEFRA, 2004-2005, GBP 70k – Prof Peter Andras (CI; Newcastle University).
  • Syntactic pattern recognition (Dr Fletcher). The aim of this project is to develop a method for robust recognition of complex recursively structured geometric patterns, in the presence of noise, vagueness, occlusion, distortion and overlapping of patterns. For examples see http://www.scm.keele.ac.uk/staff/p_fletcher/home/hex/hex.html

Current

  • Adam Wootton (supervisor: Dr Charles Day)
  • Mohammed Al-Janabi (supervisor: Prof Peter Andras)

Past

  • Kanida Sinmai (superviosr: Prof Peter Andras; Newcastle University, 2015)
  • Dr Nils Hammerla (supervisor: Prof Peter Andras; Newcastle University, PhD, 2014)
  • Charlotte Blackburn (supervisor: Prof Peter Andras, Newcastle University, MPhil, 2014)
  • Dr A. Ryad Soobhany (supervisor: Dr K.P. Lam, Keele University, PhD, 2013)
  • Dr John Butcher (supervisor: Dr Charles Day, Keele Univeristy, PhD, 2011)
  • Dr Kieren Lythgow (supervisor: Prof Peter Andras, Newcastle University, PhD, 2010)
  • Dr Shaun Fitch (supervisor: Prof Peter Andras, Newcastle University, PhD, 2008)
  • Fatma Eldresi (supervisor: Prof Peter Andras, Newcastle University, MPhil, 2003)
  • Ying Zhang (supervisor: Prof Peter Andras, Newcastle University,MPhil, 2004)

Past Research Associates

  • Dr Pablo Suau (supervisor: Prof Peter Andras; 2013-2014; Newcastle University; currently research associate at Newcastle University)
  • Dr Denis Besnard (supervisor: Prof Peter Andras; 2006; Newcastle University; currently research associate at Mines – Paris Tech, Toulouse)
  • Jacques Chang (supervisor: Prof Peter Andras; 2006)
  • Dr Dominic Searson (supervisor: Prof Peter Andras; 2003-2004; Newcastle University; currently senior research associate at Newcastle University)
  • Professor Anand Pandyan
  • Professor Peter Haycock
  • Dr Ata Kaban (Birmingham University)
  • Dr Lehel Csató (Babes-Bolyai University – Cluj)
  • Andrew Kelley (XACT PCB Ltd)
  • Professor Paul Watson (Newcastle University)
  • Dr Thomas Plötz (Newcastle University)