Andras Lab

Website of the lab of Professor Peter Andras

Peter Andras

I am Professor of Computer Science and Informatics in the School of Computing and Mathematics of Keele University and I am also the Head of this School.

I am interested in the understanding of information processing in complex systems. My favorite complex system is the nervous system, but I am also interested in complex software systems, protein interaction systems and social interaction systems. I try to uncover how such systems organize themselves in order to process information about their complex environment, how information is represented in their processes, how they generate their actions to gain new information from their environment, and how they evolve in the context of their environment.


Colin Reeves Building
School of Computing and Mathematics
Keele University
Keele, Newcastle-under-Lyme, Staffordshire
United Kingdom
 Tel. +44-1782-733412
Fax. +44-1782-724268

Recent papers

User Perception of Bitcoin Usability and Security across Novice Users, A AlShamsi, P Andras, International Journal of Human-Computer Studies, 126:94-110, 2019.

Trusting Intelligent Machines: Deepening Trust Within Socio-Technical Systems, P Andras, L Esterle, M Guckert, TA Han, PR Lewis, K Milanovic, T Payne, C Perret, J Pitt, ST Powers, N Urquhart, S Well, IEEE Technology and Society Magazine, 37:76-83, 2018.

Social learning in repeated cooperation games in uncertain environments, P Andras, Cognitive Systems Research, 51:24-39, 2018.

  High-dimensional function approximation with neural networks for large volumes of data, P Andras, IEEE Transactions on Neural Netowkrs and Learning Systems, 29:500-508, 2018.

Measuring and testing the scalability of cloud-based software services, A Al-Said Ahmad, P Andras, IEEE World Congress on Services (SERVICES), pp.67-74, 2018.

Random Projection Neural Network Approximation, P Andras, International Joint Conference on Neural Networks (IJCNN), 2018.

 Cooperation in Repeated Rock-Paper-Scissors Games in Uncertain Environments, PAndras, Artificial Life Conference (ALife), pp.404-411, 2018

Locally Excited State–Charge Transfer State Coupled Dyes as Optically Responsive Neuron Firing Probes, D Sirbu, JB Butcher, PG Waddell, P Andras, AC Benniston, Chemistry–A European Journal, 23: 14639-14649, 2017. 

Analysis of the dynamics of temporal relationships of neural activities using optical imaging data. (Steyn, JS, Andras, P, Journal of Computational Neuroscience, 42: 107-121, 2017.)

Optogenetics in silicon: a neural processor for predicting optically active neural networks. (Luo, L, Nikolic, P, Evans, B, Andras, P, Yakovlev, A, Degenaar, P, IEEE Transactions on Biomedical Circuits and Systems, 11: 15-27, 2017.)

Unsupervised home monitoring of Parkinson's disease motor symptoms using body-worn accelerometers.  (Fisher, JM, Hammerla, NY, Ploetz, T, Andras, P, Rochester, L, Walker, RW, Parkinsonism & Related Disorders, 33: 44-50, 2016).

Assessing the acceptability of body-worn sensors for monitoring of Parkinson's Disease patients  (JM Fisher, NY Hammerla, L Rochester, P Andras, RW Walker, Telemedicine and e-Health, 22: 1-7, 2016.)

 Approximation of high-dimensional functions (P Andras, Neural Networks and Learning Systems, IEEE Transactions on 25 (3), 495-505, 2014.)

Social learning, environmental adversity and the evolution of cooperation. (Andras, P, Artificial Life Conference (ALife) 2016.)

Modelling the restoration of activity in a biological neural network. (Dos Santos, F, Steyn, JS, Andras, P, International Joint Conference on Neural Networks (IJCNN) 2016.)

A critical analysis of studies that address the use of text mining for citation screening in systematic reviews. (Olorisade, BK, De Quincey, E, Brereton, P, Andras, P, 20th International Conference on Evaluation and Assessment in Software Engineering (EASE) 2016.)

The Trade-off between Usability and Security in the Context of eGovernment: A Mapping Study. (Alshamsi, A, Williams, N, Andras, P, British HCI 2016 Conference, 2016.)

Modelling the evolution of successful human populations (P Andras, European Conference on Artificial Life 2015, pp.130-137.)

Deep learning assessment of the state of Parkinson's Disease patients (NY Hammerla, JM Fisher, P Andras, L Rochester, R Walker, T Plötz, Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015.)