Shirin Dora is a Senior Lecturer in Neuromorphic Computing in the Department of Computer Science at Loughborough University. His primary area of research is developing learning algorithms for Spiking Neural Networks (SNN) and applying these networks for AI in energy-constrained scenarios like onboard satellites. He completed his PhD from Nanyang Technological University in Singapore on the topic of developing biologically plausible learning approaches for spiking neural networks. After his PhD, he pursued post-doctoral research in computational neuroscience at the cognitive and systems neuroscience group at the University of Amsterdam. From October, 2019 to September, 2021, he was a Lecturer of Data Analytics in the Intelligent Systems Research Centre at Ulster University in United Kingdom.
Research areas
My research interests include energy-efficient AI for edge-computing. In particular, I focus on bio-inspired mechanisms for learning which include spiking neural networks and predictive coding. On the applied side, I am interested in research on applying AI onboard satellites.
Member of organising committee for Annual Computational Neuroscience Meeting 2020, 2021.
Below are some of my recent publications. For an updated list, please check my scholar page.
- Dora, S., Bohte, S. M., & Pennartz, C. (2021). Deep Gated Hebbian Predictive Coding Accounts for Emergence of Complex Neural Response Properties Along the Visual Cortical Hierarchy. Frontiers in Computational Neuroscience, 65.
- Machingal, P., Thousif, M., Dora, S., & Sundaram, S.. Self-regulated Learning Algorithm for Distributed Coding Based Spiking Neural Classifier. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-7). IEEE.
- Saranirad, V., McGinnity, T.M., Dora, S., & Coyle, D.. DoB-SNN: A New Neuron Assembly-inspired Spiking Neural Network for Pattern Classification. In 2021 International Joint Conference on Neural Networks (IJCNN).