Peter Andras
peter andras

Prof Peter Andras

Dean of School of Computing Engineering and the Built Environment

 0131 455 2456

  P.Andras@napier.ac.uk

  

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 Society (INNS), Fellow of the Royal Society of Biology, Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and member of the UK Computing Research Committee (UKCRC), IEEE Computer Society, Society for Artificial Intelligence and Simulation of Behaviour (AISB), International Society for Artificial Life (ISAL) and the Society for Neuroscience (SfN).

Peter serves on the EPSRC Peer Review College, the Royal Society International Exchanges Panel and the Royal Society 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.

School

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

 

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163 results

Social learning in repeated cooperation games in uncertain environments

Journal Article
Andras, P. (2018)
Social learning in repeated cooperation games in uncertain environments. Cognitive Systems Research, 51, 24-39. https://doi.org/10.1016/j.cogsys.2018.04.013
Cooperation and social learning are fundamental mechanisms that maintain social organisation among animals and humans. Social institutions can be conceptualised abstractly as ...

Reproducibility in machine Learning-Based studies: An example of text mining

Conference Proceeding
Olorisade, B. K., Brereton, P., & Andras, P. (2017)
Reproducibility in machine Learning-Based studies: An example of text mining. In ICML 2017 RML Workshop: Reproducibility in Machine Learning
Reproducibility is an essential requirement for computational studies including those based on machine learning techniques. However, many machine learning studies are either n...

A robust data-driven approach to the decoding of pyloric neuron activity

Conference Proceeding
dos Santos, F., Andras, P., Collins, D., & Lam, K. (2017)
A robust data-driven approach to the decoding of pyloric neuron activity. In 2017 IEEE International Workshop on Signal Processing Systems (SiPS). https://doi.org/10.1109/SiPS.2017.8110017
The combination of intra and extra-cellular recording of small neuronal circuits such as stomatogastric nervous systems of the crab (Cancer borealis) is well documented and ro...

Towards an Accurate Identification of Pyloric Neuron Activity with VSDi

Conference Proceeding
dos Santos, F., Andras, P., & Lam, K. (2017)
Towards an Accurate Identification of Pyloric Neuron Activity with VSDi. In Artificial Neural Networks and Machine Learning – ICANN 2017 (121-128). https://doi.org/10.1007/978-3-319-68600-4_15
Voltage-sensitive dye imaging (VSDi) which enables simultaneous optical recording of many neurons in the pyloric circuit of the stomatogastric ganglion is an important techniq...

A multiresolution approach to the extraction of the pyloric rhythm

Conference Proceeding
dos Santos, F., Andras, P., & Lam, K. (2017)
A multiresolution approach to the extraction of the pyloric rhythm. In 2017 40th International Conference on Telecommunications and Signal Processing (TSP) (403-406). https://doi.org/10.1109/TSP.2017.8076015
This paper describes our work toward the development of a computationally robust methodology to identify the pyloric neurons in the stomatogastric ganglion of Cancer pagurus u...

Locally Excited State–Charge Transfer State Coupled Dyes as Optically Responsive Neuron Firing Probes

Journal Article
Sirbu, D., Butcher, J. B., Waddell, P. G., Andras, P., & Benniston, A. C. (2017)
Locally Excited State–Charge Transfer State Coupled Dyes as Optically Responsive Neuron Firing Probes. Chemistry - A European Journal, 23(58), 14639-14649. https://doi.org/10.1002/chem.201703366
A selection of NIR-optically responsive neuron probes was produced comprising of a donor julolidyl group connected to a BODIPY core and several different styryl and vinylpyrid...

Open-ended evolution in cellular automata worlds

Conference Proceeding
Andras, P. (2017)
Open-ended evolution in cellular automata worlds. In ECAL 2017, the Fourteenth European Conference on Artificial Life (438-445). https://doi.org/10.1162/isal_a_073
Open-ended evolution is a fundamental issue in artificial life research. We consider biological and social systems as a flux of interacting components that transiently partici...

A systematic mapping study of empirical studies on software cloud testing methods

Conference Proceeding
Ahmad, A. A., Brereton, P., & Andras, P. (2017)
A systematic mapping study of empirical studies on software cloud testing methods. In 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) (555-562). https://doi.org/10.1109/QRS-C.2017.94
Context: Software has become more complicated, dynamic, and asynchronous than ever, making testing more challenging. With the increasing interest in the development of cloud c...

Using supervised machine learning algorithms to detect suspicious URLs in online social networks

Conference Proceeding
Al-Janabi, M., Quincey, E. D., & Andras, P. (2017)
Using supervised machine learning algorithms to detect suspicious URLs in online social networks. In ASONAM '17: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 (1104-1111). https://doi.org/10.1145/3110025.3116201
The increasing volume of malicious content in social networks requires automated methods to detect and eliminate such content. This paper describes a supervised machine learni...

A systematic analysis of random forest based social media spam classification

Conference Proceeding
Al-Janabi, M., & Andras, P. (2017)
A systematic analysis of random forest based social media spam classification. In Network and System Security: 11th International Conference, NSS 2017, Helsinki, Finland, August 21–23, 2017, Proceedings (427-438). https://doi.org/10.1007/978-3-319-64701-2_31
Recently random forest classification became a popular choice machine learning applications aimed to detect spam content in online social networks. In this paper, we report a ...

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