Peter Andras
peter andras

Prof Peter Andras

Dean of School of Computing Engineering and the Built Environment

Biography

Professor Peter Andras is the Dean of the Schools of Computing and Engineering & the Built Environment since August 2021.

Previously Peter was the Head of the School of Computing and Mathematics (2017 – 2021) and Professor of Computer Science and Informatics at Keele University from 2014 – 2021. Prior to this he worked at Newcastle University in the School of Computing (2002 – 2014) and the Department of Psychology (2000 – 2002).

He has a PhD in Mathematical Analysis of Artificial Neural Networks (2000), MSc in Artificial Intelligence (1996) and BSc in Computer Science (1995), all from the Babes-Bolyai University, Romania.

Peter’s research interests span a range of subjects including artificial intelligence, machine learning, complex systems, agent-based modelling, software engineering, systems theory, neuroscience, modelling and analysis of biological and social systems. He has worked on many research projects, mostly in collaboration with other researchers in computer science, psychology, chemistry, electronic engineering, mathematics, economics and other areas. His research projects have received around £2.5 million funding, his papers have been cited by over 2,400 times and his h-index is 25 according to Google Scholar.

Peter has extensive experience of working with industry, including several KTP projects and three university spin-out companies, one of which is on the London Stock Exchange since 2007 – eTherapeutics plc.

Peter is member of the Board of Governors of the International Neural Network Âé¶¹ÉçÇø (INNS), Fellow of the Royal Âé¶¹ÉçÇø of Biology, Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and member of the UK Computing Research Committee (UKCRC), IEEE Computer Âé¶¹ÉçÇø, Âé¶¹ÉçÇø for Artificial Intelligence and Simulation of Behaviour (AISB), International Âé¶¹ÉçÇø for Artificial Life (ISAL) and the Âé¶¹ÉçÇø for Neuroscience (SfN).

Peter serves on the EPSRC Peer Review College, the Royal Âé¶¹ÉçÇø International Exchanges Panel and the Royal Âé¶¹ÉçÇø APEX Awards Review College. He is also regularly serving as review panel member and project assessor for EU funding agencies.

Outside academia, Peter has an interest in politics and community affairs. He served as local councillor in Newcastle upon Tyne, parish councillor in Keele and stood in general elections for the Parliament. He has experience of working with and leading community organisations and leading a not-for-profit regional development consultancy and project management organisation.

Esteem

Grant Funding Panel Member

  • EPSRC grant panel member
  • EU Horizon 2020 / Horizon Europe / FP6 / FP7 grant panel member
  • Austria FIT IT grant panel member

 

Grant Reviewer

  • Leverhulme Trust grant reviewer
  • MRC grant reviewer
  • Austria FIT IT grant reviewer
  • BBSRC grant reviewer
  • EPSRC grant reviewer
  • EU Horizon 2020 / Horizon Europe / FP6 / FP7 grant reviewer

 

Date


165 results

Efficient selection of the node parameters in RBF neural networks

Conference Proceeding
Andras, P. (1999)
Efficient selection of the node parameters in RBF neural networks. In Seminar of Numerical and Statistical Calculus (9-22

Approximation of chaotic shapes with tree-structured neural networks

Conference Proceeding
Andras, P. (1999)
Approximation of chaotic shapes with tree-structured neural networks. In IJCNN'99: International Joint Conference on Neural Networks, Proceedings (817-820). https://doi.org/10.1109/IJCNN.1999.831056
The approximation of highly irregular decision regions is a challenging problem in pattern recognition and classification. Existing neural networks require many neurons for ap...

Orthogonal RBF neural network approximation

Journal Article
Andras, P. (1999)
Orthogonal RBF neural network approximation. Neural Processing Letters, 9, 141-151. https://doi.org/10.1023/A%3A1018621308457
The approximation properties of the RBF neural networks are investigated in this paper. A new approach is proposed, which is based on approximations with orthogonal combinatio...

Amnesia: Neuropsychological Interpretation and Artificial Neural Network Simulation

Journal Article
Opre, A., & Andras, P. (1998)
Amnesia: Neuropsychological Interpretation and Artificial Neural Network Simulation. Cognition, Brain, Behavior: An Interdisciplinary Journal, 2(3-4), 315-335
The amnesia syndrome is characterized by normal perceptual, linguistic and intellectual functioning together with an inability to remember explicitly recent events and new inf...

A genetic solution for the cutting stock problem

Conference Proceeding
András, P., András, A., & Szabό, Z. (1996)
A genetic solution for the cutting stock problem. In Proceedings of the First Online Workshop on Soft Computing (WSC1) (87-92
The cutting stock problem it is of great interest in relation with several real world problems. Basically it means that there are some smaller pieces that have to be cut from ...

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