Evolving Spiking Neural Networks for Spatio- and Spectro-Temporal Data Analysis: Models, Implementations, Applications.
My Ph.D. looked at the applications of large-scale probabilistic computational spiking neural network modelling for spatio-temporal pattern recognition. I introduced design theory and high-performance computing implementations of these networks, and showed how they are a superior approach to addressing the problem of complex adaptive pattern recognition. Practical applications were explored, including in stroke rehabilitation and radioastronomy.
During this work, I was able to publish and share my work in a number of different forums, including as an invited lecturer at the IEEE CIS Summer School on Neuromorphic and Cyborg Intelligent Systems, and workshop leader at international conferences such as INNS Big Data and the Capo Caccia CSN Workshop. Articles directly related to my thesis have won several best paper awards, most notably being recognised as the best paper for 2016 in the Neural Networks Journal, and as best paper in the IEEE 8th International Conference on Intelligent Systems. I was also honoured to organise and chair multiple international A/A* rated conference special sessions, including at WCCI, IJCNN, and ICONIP conferences.
My thesis can be accessed here.
Please note that this publication list is not necessarily up to date.
Sengupta, N., Ramos, J.I., Tu, E., Marks, S., Scott, N., Weclawski, J., Gollahalli, A.R., Doborjeh, M.G., Doborjeh, Z.G., Kumarasinghe, K., Breen, V., Abbott, A. (2018). From von Neumann Architecture and Atanasoffs ABC to Neuro-Morphic Computation and Kasabov’s NeuCube: Principles and Implementations. Learning Systems: From Theory to Practice. Springer. doi:10.1007/978-3-319-75181-8_1
Kasabov, N., Scott, N., Tu, E., Marks, S., Sengupta, N., Capecci, E., Othman, M., Doborjeh, M., Murli, N., Hartono, R., Espinosa-Ramos, J.I., Zhou, L., Alvi, F., Wang, G., Taylor, D., Feigin, V., Gulyaev, S., Mahmoud, M., Hou, Z.-G. and Yang, J. (2015). Evolving Spatio-Temporal Data Machines Based on the NeuCube Neuromorphic Framework: Design Methodology and Selected Applications. Neural Networks. Special Issue on Learning in Big Data. Elsevier. doi:10.1016/j.neunet.2015.09.011
Sengupta, N., Ramos, J.I., Tu, E., Marks, S., Scott, N., Weclawski, J., Gollahalli, A.R., Doborjeh, M.G., Doborjeh, Z.G., Kumarasinghe, K., Breen, V., Abbott, A. (2018). From von Neumann Architecture and Atanasoffs ABC to Neuro-Morphic Computation and Kasabov’s NeuCube: Principles and Implementations. In IEEE 8th International Conference on Intelligent Systems. IEEE.
Sengupta, N., Scott, N., and Kasabov, N. (2015). Framework For Knowledge Driven Data Encoding For Brain Data Modelling Using Spiking Neural Network Architecture. In 5th International Conference on Fuzzy and Neural Computing. 17-19 December 2015. Hyderabad, India. Springer.
Taylor, D., Chamberlain, J., Signal, N., Scott, N., Kasabov, N., Capecci, E., Tu, E., Saywell, N., Chen, Y., Hu, J., and Hou, Z.-G. (2015). Brain-Computer Interfaces in Neuro Rehabilitation. In 13th International Conference on Neuro-Computing and Evolving Intelligence. February 19-20, Auckland, New Zealand.
Scott, N., Mahmoud, M., Hartono, R., Gulyaev, S., and Kasabov, N. (2015). Feasibility analysis of using the NeuCube Spiking Neural Network Architecture for Dispersed Transients and Pulsar Detection. In 13th International Conference on Neuro-Computing and Evolving Intelligence. February 19-20, Auckland, New Zealand.
Scott, N., and Kasabov, N. (2015). Feasibility of Implementing NeuCube on the SpiNNaker Neuromorphic Hardware Device. In 13th International Conference on Neuro-Computing and Evolving Intelligence. February 19-20, Auckland, New Zealand.
Marks, S., Estevez, J. E., and Scott, N. (2015). Immersive Visualisation of 3-Dimensional Neural Network Structures. In 13th International Conference on Neuro-Computing and Evolving Intelligence. February 19--20, Auckland, New Zealand.
Hu, J., Hou, Z.-G., Chen, Y., Kasabov, N., and Scott, N. (2014). EEG-Based Classification of Upper-Limb ADL Using SNN for Active Robotic Rehabilitation. In Proceedings of the 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics. Sao Paulo, Brasil. IEEE. doi:10.1109/BIOROB.2014.6913811
Taylor, D., Scott, N., Kasabov, N., Tu, E., Capecci, E., Saywell, N., Chen, Y., Hu, J., and Hou, Z.-G. (2014) Feasibility of the NeuCube SNN architecture for detecting motor execution and motor intention for use in BCI applications. In Proceedings of the IEEE International Joint Conference on Neural Networks. Beijing, China. IEEE. doi:10.1109/IJCNN.2014.6889936
Kasabov, N., Hu, J., Chen, Y., Scott, N., and Turkova, Y. (2013). Spatio-Temporal EEG Data Classification in the NeuCube 3D SNN Environment. In LNCS 8828, Proceedings of the 20th International Conference on Neural Information Processing, pages 63-69. Daegu, Korea. Springer. doi:10.1007/978-3-642-42051-1_9
Scott, N., Kasabov, N., and Indiveri, G. (2013). NeuCube Neuromorphic Framework for Spatio-Temporal Brain Data and its Python Implementation. In LNCS 8828, Proceedings of the 20th International Conference on Neural Information Processing, pages 78-84. Daegu, Korea. Springer. doi:10.1007/978-3-642-42051-1_11
Scott, N. (2015). Scientific Research Collaboration in the Asia-Pacific Region: Challenges and Opportunities. Invited Talk for the Asia New Zealand Foundation. Auckland, New Zealand.
Scott, N., Indiveri, G., Davidson, S. (2015). Neucube on High Performance Neuromorphic Computers. 13th International Conference on Neuro-Computing and Evolving Intelligence. Auckland, New Zealand.
Scott, N., Hartono, R., Mahmoud, M., Gulyaev, S., and Kasabov, N. (2015). Neuromorphic Computing with NeuCube for Dispersed Transients and Pulsar Detection. Computing for SKA (C4SKA) Colloquium. Auckland, New Zealand.
Scott, N. (2014). Spiking Neural Networks for Personalised and Predictive Medicine. School of Pharmacy, Faculty of Medical and Health Sciences, University of Auckland. Auckland, New Zealand.
Kasabov, N., and Scott, N. (2014). Machine Learning and Predictive Modelling for Large Stream Data using Neuromorphic Computation. International Neural Network Society 'Big Data and Neural Networks' Special Talks event. Beijing, China.
Scott, N. (2014). Building the NeuCube: Tools and Techniques for Neuromorphic Simulation in silico. State Key Laboratory of Management and Control for Complex Systems, Institute for Automation, Chinese Academy of Sciences, Beijing, China.
Scott, N. (2014). Neuromorphic Computation for Dispersed Transient and Pulsar Search with the Square Kilometre Array. Jodrell Bank Center for Astrophysics, University of Manchester. Manchester, U.K.
Kasabov, N., Scott, N., Pears, R., Hartono, R., and Gulyaev, S. (2014). Predictive Data Modelling of Large and Fast Streams of Spatio- or Spectro -Temporal Data using Neuromorphic Computation. Computing for Square Kilometre Array Workshop, Multicore World 2014. Auckland, New Zealand.
Scott, N. (2013). Neuromorphic Computing for Spatio- and Spectro-Temporal Pattern Recognition of Neuroinformatics Data: Applications in Neurorehabilitation. Institute for Automation, Chinese Academy of Sciences. Beijing, China.
Scott, N. and Kasabov, N. (2016) Spiking Neural Networks: The Machine Learning Approach. Invited Tutorial at the International Joint Conference on Neural Networks, World Congress on Computational Intelligence. Vancouver, Canada.
Scott, N. (2015). Spiking Neural Networks for Machine Learning and Predictive Data Modelling: Methods, Systems, Applications. Invited Lecture and Tutorial Session at the IEEE Computational Intelligence Society Summer School on Neuromorphic and Cyborg Intelligent Systems. Hangzhou, China.
Kasabov, N., Scott, N. (2014). Spiking Neural Networks for Machine Learning and Predictive Data Modelling: Methods, Systems, Applications. 2014 IEEE World Congress on Computational Intelligence, International Joint Conference on Neural Networks. Beijing, China.
Special Session Chair, Spiking Neural Networks. IEEE World Congress on Computational Intelligence, International Joint Conference on Neural Networks. Vancouver, Canada. 2016.
Poster and Demonstration Session Chair, 13th International Conference on Neuro-Computing and Evolving Intelligence (NCEI '15). Auckland, New Zealand. 2015.
Special Session Chair, Spiking Neural Networks. IEEE World Congress on Computational Intelligence, International Joint Conference on Neural Networks. Beijing, China. 2014.
Special Session Chair, Spiking Neural Networks. 20th International Conference on Neural Information Processing. Daegu, Korea. 2013.
Kasabov, N., Modha, D., and Scott, N. (2015). Spiking Neural Networks and Neuromorphic Data Machines. Workshop Session at the INNS Big Data Conference 2015. San Francisco, USA.
Scott, N. (2012). Group Session Chair, Pattern Association and Learning in Computational Models of Spiking Neural Networks. CSN Cognitive Neuromorphic Engineering Workshop. Capo Caccia, Sardinia, Italy.
Two Masters (Computer and Information Sciences) thesis students completed. Joint supervised with N. Kasabov and D. Taylor (FMHS, AUT).
Special Session Organising Chair, "Spiking Neural Networks". IEEE World Congress on Computational Intelligence, International Joint Conference on Neural Networks. Vancouver, Canada. 2016.
Special Session Organising Chair, "Spiking Neural Networks". 20th International Conference on Neural Information Processing. Daegu, Korea. 2013.
Organising Committee. Workshop on "Spiking Neural Networks and Neuromorphic Data Machines". INNS Conference on Big Data, 8-10 August 2015. San Francisco, USA.
Organising Committee. 13th International Conference on Neuro-Computing and Evolving Intelligence 2015 (NCEI '15), 19-20 February 2015. Auckland, New Zealand.
Special Session Organising Chair, "Spiking Neural Networks". 20th International Conference on Neural Information Processing. Daegu, Korea. 2013.
Advanced Processor Technologies Group, School of Computer Science, The University of Manchester. Manchester, UK. April 2014.
State Key Laboratory of Management and Control for Complex Systems, Institute for Automation, Chinese Academy of Sciences, Beijing, China. October-November 2013.