Andras Lab

Website of the lab of Professor Peter Andras

Peter Andras

I am Professor of Computer Science and Director of the Andras Lab.

I am a Visiting Fellow in the Edinburgh College of Art at the University of Edinburgh.

I was the  Dean of the School of Computing, Engineering & Built Environment at Edinburgh Napier University (2021-26), the Head of School of Computing and Mathematics (2017-21) and the Head of Computing (2014-17) at Keele University, the Director of Postgraduate Research and Programmes (2010-14) and Reader (2005-14) and Lecturer (2002-05) in the School of Computing and Lecturer (2001-02) and Researcher (2000-01) in the Department of Psychology at Newcastle University.

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.

 
 
Email:
peter@peter-andras-lab.org
peter.andras.ncl@gmail.com
v1pandra@ed.ac.uk

Recent papers

Machine learning models based on routinely sampled blood tests can predict the presence of malignancy amongst patients with suspected musculoskeletal malignancy. Bentick, K, Runevic, J, Akula, S, Kyriacou, T, Cool, P, Andras, P , Methods 220, 55-60, 2023.

Structural Complexity and Performance of Support Vector Machines. BK Olorisade, P Brereton, P Andras,   Proceedings of the 2022 International Joint Conference on Neural Networks (IJCNN), 2022.

Where do successful populations originate from? Andras, P and Stanton, A, Journal of Theoretical Biology, 524: 110734, 2021.

Cloud-based Software Services Delivery from the Perspective of Scalability. Al-Said Ahmad, A, Andras, P,  International Journal of Parallel, Emergent and Distributed Systems, 36: 53-68, 2021.

A review of privacy-preserving federated learning for the Internet-of-Things In: In: Habib ur Rehman, M and Medhat Gaber, M (eds.) Federated Learning Systems: Towards Next Generation AI, Springer's Series on Studies in Computational Intelligence, Springer, Cham, Briggs, C, Fan, Z, Andras, P, pp.21-50, 2021.

Composition of Games as a Model for the Evolution of Social Institutions. Andras, P, Proceedings of the Artificial Life Conference – 2020, pp.171-179, 2020.

Federated learning with hierarchical clustering of local updates to improve training on non-IID data. Briggs, C, Fan, Z, Andras, P, Proceedings of the 2020 International Joint Conference on Neural Networks (IJCNN), 2020.

Scalability Analysis Comparisons of Cloud-based Software Services. Al-Said Ahmad, A, Andras, P, Journal of Cloud Computing, 8: 1-17, 2019.

The use of bibliography enriched features for automatic citation screening. Olorisade, BK, Brereton OP, Andras, P, Journal of Biomedical Informatics, 94: 103202, 2019.

Environmental Harshness and Fitness Improving Innovations. Andras, P, Proceedings of the Artificial Life 2019 (ALife 2019), pp. 300-307, 2019.

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.