Dr Shadi Abpeikar

Postdoctoral Fellow
School of Engineering and Information Technology
  • ABOUT
  • PUBLICATIONS

Shadi Abpeikar is a research associate in the School of Engineering and Information Technology at the University of New South Wales, Canberra, under the supervision of A/Prof Kathryn Kasmarik. 

Shadi completed her Bachelor in Applied Mathematics in Iran. She got her Master and PhD in Computer Science from the AmirKabir University of Technology in Iran, in 2013 and 2019, respectively. She received the award of the highest graduation score of a bachelor degree from Iran University of Science and Technology in 2011, and the award of the best master thesis of the department of mathematics and computer science of the AmirKabir University of Technology in 2013. Also, Shadi completed her sabbatical research at the University of Udine, in Italy in 2017. She started her career as a research associate at the University of New South Wales in July 2019. Her technical skills are computer programming with C#, Python, Java, Android, MATLAB, and HTML.  Also, her research interests are machine learning, swarm robotics, swarm intelligence algorithms, big data, feature selection, decision support systems, neural networks, neural trees and intelligent transportation systems. 

Journal articles

Abpeikar S; Ghatee M; Foresti GL; Micheloni C, 2020, 'Adaptive neural tree exploiting expert nodes to classify high-dimensional data', Neural Networks, vol. 124, pp. 20 - 38, http://dx.doi.org/10.1016/j.neunet.2019.12.029

Abpeykar S; Ghatee M, 2019, 'Neural trees with peer-to-peer and server-to-client knowledge transferring models for high-dimensional data classification', EXPERT SYSTEMS WITH APPLICATIONS, vol. 137, pp. 281 - 291, http://dx.doi.org/10.1016/j.eswa.2019.07.003

Abpeykar S; Ghatee M, 2019, 'An ensemble of RBF neural networks in decision tree structure with knowledge transferring to accelerate multi-classification', NEURAL COMPUTING & APPLICATIONS, vol. 31, pp. 7131 - 7151, http://dx.doi.org/10.1007/s00521-018-3543-9

Abpeykar S; Ghatee M; Zare H, 2019, 'Ensemble decision forest of RBF networks via hybrid feature clustering approach for high-dimensional data classification', COMPUTATIONAL STATISTICS & DATA ANALYSIS, vol. 131, pp. 12 - 36, http://dx.doi.org/10.1016/j.csda.2018.08.015

Abpeykar S; Ghatee M, 2018, 'Decent direction methods on the feasible region recognized by supervised learning metamodels to solve unstructured problems', JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES, vol. 39, pp. 1245 - 1262, http://dx.doi.org/10.1080/02522667.2017.1324588

Abpeykar S; Ghatee M, 2014, 'Supervised and unsupervised learning DSS for incident management in intelligent tunnel: A case study in Tehran Niayesh tunnel', TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, vol. 42, pp. 293 - 306, http://dx.doi.org/10.1016/j.tust.2014.03.008

Abpeykar S; Ghatee M, 'A real-time decision support system for bridge management based on the rules generalized by CART decision tree and SMO algorithms', , http://arxiv.org/abs/1803.01412v2

Conference Papers

Kasmarik K; Abpeikar S; Khan MM; Khattab N; Barlow M; Garratt M, 2020, 'Autonomous Recognition of Collective Behaviour in Robot Swarms', Canberra, Australia, presented at 33rd Australasian Joint Conference on Artificial Intelligence, Canberra, Australia, 29 November 2020