Associate Professor Mark D. McDonnell

Adjunct Associate Professor UniSA STEM

Mawson Lakes Campus (W1-19)
tel +61 8 830 23341

email Mark.McDonnell@unisa.edu.au

Research Degree Supervisor

About me

Deep neural networks
Machine learning
Data science
Computational neuroscience

A/Prof. Mark McDonnell is now Adjunct Associate Professor at UniSA, and is no longer supervising new PhD students.

My interests are primarily in machine learning, with a focus on its intersections between data science, electronic engineering and neuroscience.

For my Google Scholar page see here

For my Linked-In profile see here

A/Prof. McDonnell's research expertise is in (i) machine learning applied to computer vision, autonomous decision making, and sequence recognition; and (ii) computational modeling of random variability in nonlinear systems, with applications in neuroscience and biomedical engineering. I have published over 120 refereed papers in these areas, including several review articles, a Cambridge University... Read more

UniSA STEM

Harnessing connections across science, technology, engineering and mathematics, UniSA STEM creates innovative solutions and groundbreaking developments across teaching, learning and research.

Tweets by @UniversitySA

Research

Highlights

Applied Machine Learning research:

Industry-standard computer-vision systems (partners include Consilium Technology, Sage Automation, Container Desposit Systems)
Terrain segmentation and classification on Mars using HiRISE high-resolution satellite imagery
Epilepsy-onset prediction (collaboration with University of Melbourne and IBM)

Deep Neural Networks research:

Low-complexity/low-memory training of deep neural networks for image classification (collaboration with University of Sydney and Western Sydney University); Training wide residual networks for deployment using a single bit for each weight

Computational Neuroscience Research:

Convolutional neual network insights on the receptive fields learned in DM area cortical... Read more

Research

Projects

Excludes commercial-in-confidence projects.

ARC ITTC in Cognitive Computing for Medical Technologies, ARC - Industrial Transformation Training Centres, 13/12/2017 - 07/06/2023
Cwth Dept of Defence - Defence Support Group Scholarship, Cwth Dept of Defence - Defence Support Group, 01/01/2017 - 30/06/2021
Cwth Dept of Defence - Defence Support Group Scholarship, Cwth Dept of Defence - Defence Support Group, 15/11/2016 - 01/05/2020
Hierarchical information processing in the primate visual cortex, ARC - Discovery Projects, 01/01/2017 - 31/03/2020
Machine Learning Methods for Better Hospital Patient Management, Alcidion Corporation Pty Ltd, 05/02/2018 - 04/02/2019
Second Extension of Vision System for Container Recycling, SAGE Automation Pty Ltd, 01/02/2018 - 31/01/2019
Gov - Geospatial Artificial Intelligence for Agriculture Ph1 Viticulture, Cwth Dept of Industry, Science, Energy and Resources, 03/01/2018 - 03/01/2019
Multi-object tracking and classification for omnidirectional vision systems, Defence Science & Technology Organisation, 21/06/2016 - 28/12/2018
Ind - Geospatial Artificial Intelligence for Agriculture Ph1 Viticulture, Consilium Technology Pty Ltd, 03/01/2018 - 18/12/2018
Anomaly Detection in Satellite Communications Networks, Cwth Dept of Defence, 24/03/2017 - 28/02/2018
Improving the Identification and Management of Complex Patients using Machine Learning, Cwth Dept Industry, Science, Energy & Resources, 09/11/2016 - 30/12/2017
Improving the Identification and Management of Complex Patients using Machine Learning, Alcidion Corporation Pty Ltd, 11/11/2016 - 30/12/2017
Enhancing Speech Recognition Performance in KALDI using Deep Recurrent Neural Networks, Defence Science & Technology Organisation - Business & Commercialisation Office, 11/02/2016 - 01/06/2017
Vision System for Container Recycling - GOV RC53887, Cwth Dept Industry, Science, Energy & Resources, 01/11/2016 - 31/05/2017
Vision System for Container Recycling - IND RC53887, SAGE Automation Pty Ltd, 26/10/2016 - 31/05/2017
Multi-object visual detection, tracking and classification algorithms, Defence Science & Technology Organisation - Business & Commercialisation Office, 15/02/2013 - 31/12/2016
Persistent firing in cortical interneurons: mechanisms and potential anticonvulsant role, NHMRC - Project Grant, 01/11/2013 - 31/10/2016
Communication and information storage mechanisms in complex dynamical brain networks, ARC - Discovery Projects, 01/06/2010 - 15/02/2016

Research

Outputs

Research outputs for the last seven years are shown below. To see earlier years visit ORCID, ResearcherID or Scopus

Open access indicates that an output is open access.

Highlights

Year	Output
2020	Jones, EG, Wong, S, Milton, A, Sclauzero, J, Whittenbury, H & McDonnell, MD 2020, 'The impact of pan-sharpening and spectral resolution on vineyard segmentation through machine learning', Remote Sensing, vol. 12, no. 6, pp. 1-24. Open access 19 15 2
2019	McDonnell, MD, Moezzi, B & Brinkworth, RS 2019, 'Using style-transfer to understand material classification for robotic sorting of recycled beverage containers', International Conference on Digital Image Computing: Techniques and Applications, DICTA 2019, IEEE, article no. 8945993, pp. 1-8.
2018	McDonnell, MD 2018, 'Training wide residual networks for deployment using a single bit for each weight', 2018 International Conference on Learning Representations (ICLR), University of Massachusetts Amherst, pp. 1-15. Open access 18
2016	Gunn, LJ, Chapeau-Blondeau, F, McDonnell, MD, Davis, BR, Allison, A & Abbott, D 2016, 'Too good to be true: when overwhelming evidence fails to convince', Proceedings of the Royal Society A: Mathematical Physical and Engineering Sciences, vol. 472, no. 2187, article no. 20150748, pp. 1-15. Open access 17 20 265
2011	McDonnell, MD & Ward, LM 2011, 'The benefits of noise in neural systems: bridging theory and experiment', Nature Reviews Neuroscience, vol. 12, no. 7, pp. 415-425. 497 457

Books

Year	Output
2008	McDonnell, MD, Stocks, NG, Pearce, CE & Abbott, D 2008, Stochastic resonance: from suprathreshold stochastic resonance to stochastic signal quantization, Cambridge University Press, US. 289

Chapters

Year	Output
2009	McDonnell, MD 2009, 'Applying stochastic signal quantization theory to the robust digitization of noisy analog signals', in i Visarath (ed.), Applications of nonlinear dynamics: model and design of complex systems, Springer-Verlag, Berlin, pp. 249-261. 1

Journal Articles

Year	Output
2022	McDonnell, MD, Jones, E, Schwamb, ME, Aye, K-M, Portyankina, G & Hansen, CJ 2022, 'Planet Four: a neural network's search for polar spring-time fans on Mars', Icarus, vol. 391, article no. 115308, pp. 1-20. Open access 1
2022	McKenzie, MC & McDonnell, MD 2022, 'Modern value based reinforcement learning: a chronological review', IEEE Access, vol. 10, pp. 134704-134725. Open access
2021	Boyd, C, Brown, G, Kleinig, T, Dawson, J, McDonnell, MD, Jenkinson, M & Bezak, E 2021, 'Machine learning quantitation of cardiovascular and cerebrovascular disease: a systematic review of clinical applications', Diagnostics, vol. 11, no. 3, pp. 551-584. Open access 7 5 2
2021	Gao, X, Grayden, D & McDonnell, M 2021, 'Unifying information theory and machine learning in a model of electrode discrimination in cochlear implants', PLoS One, vol. 16, no. 9, article no. e0257568, pp. 1-16. Open access 2 2
2021	Madakkatel, I, Zhou, A, McDonnell, MD & Hyppönen, E 2021, 'Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study', Scientific Reports, vol. 11, issue 1, article no. 22997, pp. 1-11. Open access 4 4
2021	Mittal, P, Condina, MR, Klingler-Hoffmann, M, Kaur, G, Oehler, MK, Sieber, OM, Palmieri, M, Kommoss, S, Brucker, S, McDonnell, MD & Hoffmann, P 2021, 'Cancer tissue classification using supervised machine learning applied to maldi mass spectrometry imaging', Cancers, vol. 13, no. 21, article no. 5388, pp. 1-16. Open access 13 12 1
2021	Nath, N, Lee, S-H, McDonnell, M & Lee, I 2021, 'The quest for better clinical word vectors: ontology based and lexical vector augmentation versus clinical contextual embeddings', Computers in Biology and Medicine, vol. 134, article no. 104433, pp. 1-11. 5 2 1
2020	Jones, EG, Wong, S, Milton, A, Sclauzero, J, Whittenbury, H & McDonnell, MD 2020, 'The impact of pan-sharpening and spectral resolution on vineyard segmentation through machine learning', Remote Sensing, vol. 12, no. 6, pp. 1-24. Open access 19 15 2
2020	Zadeh Shirazi, A, Fornaciari, E, McDonnell, MD, Yaghoobi, M, Cevallos, Y, Tello-Oquendo, L, Inca, D & Gomez, GA 2020, 'The application of deep convolutional neural networks to brain cancer images: a survey', Journal of Personalized Medicine, vol. 10, no. 4, article number 224, pp. 1-27. Open access 24 17 3
2019	Moezzi, B, Pratti, LM, Hordacre, B, Graetz, L, Berryman, C, Lavrencic, LM, Ridding, MC, Keage, HA, McDonnell, MD & Goldsworthy, MR 2019, 'Characterization of young and old adult brains: an EEG functional connectivity analysis', Neuroscience, vol. 422, pp. 230-239. Open access 24 23
2018	Moezzi, B, Schaworonkow, N, Plogmacher, L, Goldsworthy, M, Hordacre, B, McDonnell, M, Iannella, N, Ridding, M & Triesch, J 2018, 'Simulation of electromyographic recordings following transcranial magnetic stimulation', Journal of Neurophysiology, vol. 120, no. 5, pp. 2532-2541. Open access 6 6 12
2017	Cheng, C, Zhou, B, Gao, X & McDonnell, MD 2017, 'M-ary suprathreshold stochastic resonance in multilevel threshold systems with signal-dependent noise', Physica A: Statistical Mechanics and its Applications, vol. 479, pp. 48-56. 7 5
2017	Gao, X, Grayden, DB & McDonnell, MD 2017, 'Modeling electrode place discrimination in cochlear implant stimulation', IEEE Transactions on Biomedical Engineering, vol. 64, no. 9, pp. 2219-2229. Open access 6 6
2017	McDonnell, MD & Graham, BP 2017, 'Phase changes in neuronal postsynaptic spiking due to short term plasticity', PLoS Computational Biology, vol. 13, no. 9, article no. e1005634, pp. 1-26. Open access 7 6 5
2017	Wong, SC, Stamatescu, V, Gatt, A, Kearney, D, Lee, I & McDonnell, MD 2017, 'Track everything: limiting prior knowledge in online multi-object recognition', IEEE Transactions on Image Processing, vol. 26, no. 10, pp. 4669-4683. Open access 23 16 2
2017	Xu, L, Duan, F, Gao, X, Abbott, D & McDonnell, MD 2017, 'Adaptive recursive algorithm for optimal weighted suprathreshold stochastic resonance', Royal Society Open Science, vol. 4, no. 9, article no. 160889, pp. 1-12. Open access 10 5
2016	Greenwood, PE, McDonnell, MD & Ward, LM 2016, 'A Kuramoto coupling of quasi-cycle oscillators with application to neural networks', Journal of Coupled Systems and Multiscale Dynamics, vol. 4, no. 1, pp. 1-13. 7
2016	Gunn, LJ, Chapeau-Blondeau, F, McDonnell, MD, Davis, BR, Allison, A & Abbott, D 2016, 'Too good to be true: when overwhelming evidence fails to convince', Proceedings of the Royal Society A: Mathematical Physical and Engineering Sciences, vol. 472, no. 2187, article no. 20150748, pp. 1-15. Open access 17 20 265
2016	Moezzi, B, Iannella, N & McDonnell, MD 2016, 'Ion channel noise can explain firing correlation in auditory nerves', Journal of Computational Neuroscience, v. 41, no. 2, pp. 193-206. 9 9
2016	Tissera, MD & McDonnell, MD 2016, 'Deep extreme learning machines: supervised autoencoding architecture for classification', Neurocomputing, vol. 174, pt. A, pp. 42-49. 97 87 3
2016	Xu, L, Duan, F, Abbott, D & McDonnell, MD 2016, 'Optimal weighted suprathreshold stochastic resonance with multigroup saturating sensors', Physica A: Statistical Mechanics and its Applications, vol. 457, pp. 348-355. Open access 13 11
2015	Greenwood, PE, McDonnell, MD & Ward, LM 2015, 'Dynamics of gamma bursts in local field potentials', Neural Computation, vol. 27, no. 1, pp. 74-103. Open access 13 14 3
2015	McDonnell, MD, Iannella, N, To, M-S, Tuckwell, HC, Jost, J, Gutkin, BS & Ward, LM 2015, 'A review of methods for identifying stochastic resonance in simulations of single neuron models', Network: Computation in Neural Systems, vol. 26, no. 2, pp.35-71. 5 16
2015	McDonnell, MD, Tissera, MD, Vladusich, T, Van Schaik, A & Tapson, J 2015, 'Fast, simple and accurate handwritten digit classification by training shallow neural network classifiers with the 'extreme learning machine' algorithm', PLoS One, vol. 10, no. 8, article no. e0134254, pp. 1-20. Open access 65 56 21
2015	Xu, L, Vladusich, T, Duan, F, Gunn, LJ, Abbott, D & McDonnell, MD 2015, 'Decoding suprathreshold stochastic resonance with optimal weights', Physics Letters A: General Physics, Nonlinear Science, Statistical Physics, Atomic, Molecular and Cluster Physics, Plasma and Fluid Physics, Condensed Matter, Cross-disciplinary Physics, Biological Physics, Nanosciences, Quantum Physics, vol. 379, no. 38, pp. 2277-2283. 14 10
2015	Zhou, B & McDonnell, MD 2015, 'Optimising threshold levels for information transmission in binary threshold networks: Independent multiplicative noise on each threshold', Physica A: Statistical Mechanics and its Applications, vol. 419, pp. 659-667. 8 7
2014	Gao, X, Grayden, DB & McDonnell, MD 2014, 'Stochastic information transfer from cochlear implant electrodes to auditory nerve fibers', Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, vol. 90, pp. 1-12. 7 6
2014	McDonnell, MD & Gao, X 2014, 'M-ary suprathreshold stochastic resonance: Generalization and scaling beyond binary threshold nonlinearities', Europhysics Letters: A Letters Journal Exploring the Frontiers of Physics, vol. 108, pp. 1-7. 10 7
2014	McDonnell, MD & Ward, LM 2014, 'Small modifications to network topology can induce stochastic bistable spiking dynamics in a balanced cortical model', PLoS One, vol. 9 no. 4, pp. 1-21. Open access 10 9
2014	McDonnell, MD, Boahen, K, Ijspeert, A & Sejnowski, TJ 2014, 'Engineering intelligent electronic systems based on computational neuroscience', IEEE, vol. 102, no. 5, pp. 646-651. Open access 13 10
2014	McDonnell, MD, Yaveroglu, ON, Schmerl, BA, Iannella, N & Ward, LM 2014, 'Motif-role-fingerprints : the building-blocks of motifs, clustering-coefficients and transitivities in directed networks', PLoS One, vol. 9, no. 12, pp. 1-25. Open access 14 11 2
2014	Moezzi, B, Iannella, N & McDonnell, MD 2014, 'Modeling the influence of short term depression in vesicle release and stochastic calcium channel gating on auditory nerve spontaneous firing statistics', Frontiers in Computational Neuroscience, vol. 8, article no. 163, pp. 1-12. Open access 10 10
2014	Vladusich, T & McDonnell, MD 2014, 'A unified account of perceptual layering and surface appearance in terms of gamut relativity', PLoS One, vol. 9, no. 11, pp. 1-15. Open access 1 1 3
2013	Kostal, L, Lansky, P & McDonnell, MD 2013, 'Metabolic cost of neuronal information in an empirical stimulus-response model', Biological Cybernetics: Communication and Control in Organisms and Automata, vol. 107, no. 3, pp. 355-365. 23 21 1
2013	McDonnell, MD, Li, F, Amblard, P-O & Grant, AJ 2013, 'Optimal sensor selection for noisy binary detection in stochastic pooling networks', Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, vol. 88, no. 2, pp. 1-9. Open access 6 5 1
2013	McDonnell, MD, Mohan, A & Stricker, C 2013, 'Mathematical analysis and algorithms for efficiently and accurately implementing stochastic simulations of short-term synaptic depression and facilitation', Frontiers in Computational Neuroscience, vol. 7, pp. 1-14. Open access 2 2
2013	Mohan, A, McDonnell, MD & Stricker, C 2013, 'Interaction of short-term depression and firing dynamics in shaping single neuron encoding', Frontiers in Computational Neuroscience, vol. 7, pp. 1-14. Open access 5 5
2013	Prettejohn, BJ, Berryman, MJ & McDonnell, MD 2013, 'A model of the effects of authority on consensus formation in adaptive networks : impact on network topology and robustness', Physica A: Statistical Mechanics and its Applications, vol. 392, no. 4, pp. 857-868. Open access 3 3
2013	Schmerl, BA & McDonnell, MD 2013, 'Channel-noise-induced stochastic facilitation in an auditory brainstem neuron model', Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, vol. 88, article no. 052722. Open access 21 20 1
2012	McDonnell, MD, Mohan, A, Stricker, C & Ward, LM 2012, 'Input-rate modulation of gamma oscillations is sensitive to network topology, delays and short-term plasticity', Brain Research, vol. 1434, pp. 162-177. 8 9
2011	McDonnell, MD & Ward, LM 2011, 'Natural moment-to-moment signal variability and stochastic facilitation', Nature Reviews Neuroscience, vol. 12, no. 10, pp. 612-612. Open access 1 18
2011	McDonnell, MD & Ward, LM 2011, 'The benefits of noise in neural systems: bridging theory and experiment', Nature Reviews Neuroscience, vol. 12, no. 7, pp. 415-425. 497 457
2011	McDonnell, MD 2011, 'Is electrical noise useful?', Proceedings of the Institute of Electrical and Electronics Engineers (IEEE), vol. 99, no. 2, pp. 242-246. 31 30
2011	McDonnell, MD, Grant, AJ, Land, I, Vellambi, BN, Abbott, D & Lever, K 2011, 'Gain from the two-envelope problem via information asymmetry: on the suboptimality of randomized switching', Proceedings of the Royal Society A: Mathematical Physical and Engineering Sciences, vol. 467, no. 2134, pp. 2825-2851. Open access 11 8
2011	McDonnell, MD, Ikeda, S & Manton, JH 2011, 'An introductory review of information theory in the context of computational neuroscience', Biological Cybernetics: Communication and Control in Organisms and Automata, vol. 105, no. 1, pp. 55-70. Open access 24 21
2011	Prettejohn, BJ, Berryman, MJ & McDonnell, MD 2011, 'Methods for generating complex networks with selected structural properties for simulations : a review and tutorial for neuroscientists', Frontiers in Computational Neuroscience, vol. 5, no. 11, pp. 1-18. Open access 28 49
2010	McDonnell, MD, Amblard, P-O & Stocks, NG 2010, 'Bio-inspired communication: performance limits for information transmission and compression in stochastic pooling networks with binary quantizing nodes', Journal of Computational and Theoretical Nanoscience, vol. 7, no. 5, pp. 876-883. 5 4
2010	McDonnell, MD, Burkitt, AN, Grayden, DB, Meffin, H & Grant, AJ 2010, 'A channel model for inferring the optimal number of electrodes for future cochlear implants', IEEE Transactions on Information Theory, vol. 56, no. 2, pp. 928-940. Open access 14 13
2010	McDonnell, MD, Stocks, NG & Amblard, P-O 2010, 'Communication of uncoded sensor measurements through nanoscale binary-node stochastic pooling networks', Nano Communication Networks, vol. 1, no. 3, pp. 209-223. 2
2009	McDonnell, MD & Abbott, D 2009, 'Randomized switching in the two-envelope problem', Proceedings of the Royal Society A: Mathematical Physical and Engineering Sciences, vol. 465, no. 2111, pp. 3309-3322. Open access 19 14
2009	McDonnell, MD & Abbott, D 2009, 'What is stochastic resonance? : definitions, misconceptions, debates, and its relevance to biology', PLoS Computational Biology, vol. 5, no. 5, article no. e1000348. Open access 528 497
2009	McDonnell, MD & Fliney, AP 2009, 'Signal acquisition via polarization modulation in single photon sources', Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, vol. 80, no. 6, pp. 060102.1-060102.4. Open access 2 2
2009	McDonnell, MD & Stocks, N 2009, 'Suprathreshold stochastic resonance', Scholarpedia, vol. 4, no. 6, pp. 1-9. Open access
2009	McDonnell, MD 2009, 'Information capacity of stochastic pooling networks is achieved by discrete inputs', Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, vol. 79, pp. 1-8. Open access 14 12
2009	McDonnell, MD, Amblard, P-O & Stocks, NG 2009, 'Stochastic pooling networks', Journal of Statistical Mechanics: Theory and Experiment, vol. 9, no. January. Open access 34 30
2009	Nikitin, AP, Stocks, NG, Morse, RP & McDonnell, MD 2009, 'Neural population coding is optimized by discrete tuning curves', Physical Review Letters, vol. 103, no. 13, pp. 138101.1-138101.4. Open access 35 31
2008	McDonnell, MD & Stocks, NG 2008, 'Maximally informative stimuli and tuning curves for sigmoidal rate-coding neurons and populations', Physical Review Letters, vol. 101, no. 5, pp. 1-4. Open access 45 40
2008	McDonnell, MD & Stocks, NG 2008, 'Optimal sigmoidal tuning curves for intensity encoding sensory neurons with quasi-Poisson variability', BMC Neuroscience, vol. 9, no. s1, article no. P117. Open access

Conferences

Year	Output
2020	Gao, W, Hashemi-Sakhtsari, A & McDonnell, MD 2020, 'End-to-end phoneme recognition using models from semantic image segmentation', International Joint Conference on Neural Networks, IJCNN 2020, IEEE, article no. 9207279, pp. 1-7. 1 1
2020	McDonnell, MD & Gao, W 2020, 'Acoustic scene classification using deep residual networks with late fusion of separated high and low frequency paths', IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, pp. 141-145. 47 35 3
2019	Biggs, S, Hawksley, S, McDonnell, M & Bagchi, S 2019, 'The dancer in the machine', Art Machines: International Symposium on Computational Media Art, City University of Hong Kong, pp. 1-3. Open access
2019	Chamchong, R, Gao, W & McDonnell, MD 2019, 'Thai handwritten recognition on text block-based from thai archive manuscripts', 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019, IEEE, pp. 1346-1351. 8
2019	Madakkatel, I, Chiera, B & McDonnell, MD 2019, 'Predicting financial well-being using observable features and gradient boosting', 32nd Australasian Joint Conference on Artificial Intelligence, AI 2019, Springer, pp. 228-239.
2019	McDonnell, MD, Moezzi, B & Brinkworth, RS 2019, 'Using style-transfer to understand material classification for robotic sorting of recycled beverage containers', International Conference on Digital Image Computing: Techniques and Applications, DICTA 2019, IEEE, article no. 8945993, pp. 1-8.
2019	McDonnell, MD, Mostafa, H, Wang, R & Schaik, A 2019, 'Single-bit-per-weight deep convolutional neural networks without batch-normalization layers for embedded systems', 4th Asia-Pacific Conference on Intelligent Robot Systems, IEEE, article no. 8936030, pp. 197-204. 2 2
2019	McKenzie, M & Mcdonnell, MD 2019, 'Degradation of performance in reinforcement learning with state measurement uncertainty', 2019 Military Communications and Information Systems Conference, MilCIS 2019, IEEE, article no. 8930725, pp. 1-5. 2 4
2018	Bagchi, S & McDonnell, MD 2018, 'A model of neurobiologically plausible least-squares learning in visual cortex', International Joint Conference on Neural Networks, IJCNN 2018, IEEE, vol. 2018-July, article no. 8489725, pp. 1-8.
2018	Gunn, L, Smet, P, Arbon, E & McDonnell, MD 2018, 'Anomaly detection in satellite communications systems using LSTM networks', 2018 Military Communications and Information Systems Conference (MilCIS), IEEE, pp. 1-6. Open access 7 5 3
2018	McDonnell, MD 2018, 'Training wide residual networks for deployment using a single bit for each weight', 2018 International Conference on Learning Representations (ICLR), University of Massachusetts Amherst, pp. 1-15. Open access 18
2018	Stamatescu, V & McDonnell, MD 2018, 'Diagnosing convolutional neural networks using their spectral response', in Manzur Murshed, Manoranjan Paul, Md Asikuzzaman (eds), 2018 Digital Image Computing: Techniques and Applications (DICTA), IEEE, pp. 1-8. Open access 1 1
2017	De Chazal, P & McDonnell, MD 2017, 'Regularized training of the extreme learning machine using the conjugate gradient method', 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, pp. 1802-1808. 4 4
2017	Gao, W & McDonnell, MD 2017, 'Analysis of gradient degradation and feature Map quality in deep all-convolutional neural networks compared to deep residual networks', 24th International Conference on Neural Information Processing, ICONIP 2017, Springer, pp. 612-621. 1
2017	Yousefi-Azar, M & McDonnell, MD 2017, 'Semi-supervised convolutional extreme learning machine', 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, pp.-. 9 8
2017	Yousefi-Azar, M, Hamey, L, Varadharajan, V & McDonnell, M 2017, 'Fast, automatic and scalable learning to detect android malware', International Conference on Neural Information Processing, Springer, pp. 848-857. 5
2016	McDonnell, MD, McKilliam, RG & de Chazal, P 2016, 'On the importance of pair-wise feature correlations for image classification', 2016 International Joint Conference on Neural Networks (IJCNN), IEEE, article no. 7727483, pp. 2290-2297. 3 1
2016	Padilla, D & McDonnell, MD 2016, 'Integrating convolutional neural networks into a sparse distributed representation model based on mammalian cortical learning', 2016 International Joint Conference on Neural Networks (IJCNN), IEEE, pp. 1187-1194. Open access
2016	Stamatescu, V, Wong, S, McDonnell, MD & Kearney, D 2016, 'Learned filters for object detection in multi-object visual tracking', Automatic Target Recognition XXVI, SPIE, vol. 9844, article no. 98440F, pp. 1-14. Open access 3 2
2016	Tissera, MD & McDonnell, MD 2016, 'Enhancing deep extreme learning machines by error backpropagation', in IEEE (ed.), 2016 International Joint Conference on Neural Networks (IJCNN), IEEE, article no. 7727273, pp. 735-739. 3 4
2016	Tissera, MD & McDonnell, MD 2016, 'Modular expansion of the hidden layer in single layer feedforward neural networks', International Joint Conference on Neural Networks (IJCNN), IEEE, article no. 7727571, pp. 2939-2945. 5 5
2016	Wong, SC, Gatt, A, Stamatescu, V & McDonnell, MD 2016, 'Understanding data augmentation for classification: when to warp?', 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, pp. 1-6. Open access 605 102 6
2016	de Chazal, P & McDonnell, MD 2016, 'Efficient computation of the Levenberg-Marquardt algorithm for feedforward networks with linear outputs', in IEEE (eds), 2016 International Joint Conference on Neural Networks (IJCNN), IEEE, pp. 68-75. 2 1
2015	Gao, X, Grayden, DB & McDonnell, MD 2015, 'Modeling electrode place discrimination in cochlear implants: analysis of the influence of electrode array insertion depth', 7th International IEEE/EMBS Conference on Neural Engineering, IEEE, pp. 691-694. 2 2
2015	McDonnell, MD & Vladusich, T 2015, 'Enhanced image classification with a fast-learning shallow convolutional neural network', International Joint Conference on Neural Networks, IJCNN, IEEE, article no. 7280796, pp. 1-7. Open access 74 23
2014	Gao, X, Grayden, DB & McDonnell, MD 2014, 'Inferring the dynamic range of electrode current by using an information theoretic model of cochlear implant stimulation', IEEE Informational Theory Workshop, IEEE Press. 3
2014	Gao, X, Grayden, DB & McDonnell, MD 2014, 'Using convex optimization to compute channel capacity in a channel model of cochlear implant stimulation', International Symposium on Information Theory, IEEE Press, pp. 2919-2923. 2 2
2014	McDonnell, MD 2014, 'Distributed bandpass filtering and signal demodulation in cortical network models', in V In, A Palacios & P Longhini (eds), International Conference on Theory and Application in Nonlinear Dynamics (ICAND 2012), Springer, pp. 155-166.
2014	Padilla, D & McDonnell, MD 2014, 'A neurobiologically plausible vector symbolic architecture', IEEE International Conference on Semantic Computing, IEEE Press, pp. 242-245. 3 2
2014	Tissera, MD & McDonnell, MD 2014, 'Enabling 'question answering' in the MBAT vector symbolic architecture by exploiting orthogonal random matrices', International Conference on Semantic Computing, IEEE, article no. 6882019, pp. 171-174. 2 2
2014	Wang, S, Guo, W & McDonnell, MD 2014, 'Distance Distributions for Real Cellular Networks', Conference on Computer Communications Workshops, IEEE Press, pp. 181-182. Open access 5 3
2014	Wang, S, Guo, W & McDonnell, MD 2014, 'Downlink interference estimation without feedback for heterogeneous network interference avoidance', International Conference on Telecommunications, IEEE Press, pp. 82-87. Open access 8 5
2014	Wang, S, Guo, W & McDonnell, MD 2014, 'Transmit pulse shaping for molecular communications', Conference on Computer Communications Workshops, IEEE Press, pp. 209-210. Open access 20 15
2014	Wang, S, Guo, W, Qiu, S & McDonnell, MD 2014, 'Performance of macro-scale molecular communications with sensor cleanse time', International Conference on Telecommunications, IEEE Press, pp. 363-368. Open access 12 11
2013	Gao, X, Grayden, DB & McDonnell, MD 2013, 'Information theoretic optimization of cochlear implant electrode usage probabilities', 35th annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBS), IEEE Engineering in Medicine and Biology Society, pp. 5974-5977. 7 7
2013	McDonnell, MD & Ward, LM 2013, 'Identifying positive roles for endogenous stochastic noise during computation in neural systems', 35th annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBS), IEEE Engineering in Medicine and Biology Society, pp. 5232-5235. Open access 1 1 1
2013	Padilla, D, Brinkworth, R & McDonnell, MD 2013, 'Performance of a hierarchical temporal memory network in noisy sequence learning', 2013 IEEE International Conference on Computational Intelligence and Cybernetics (CyberneticsCom), IEEE, pp. 45-51. 15 12 3
2012	Moroz, AS, McDonnell, MD, Burkitt, AN, Grayden, DB & Meffin, H 2012, 'Information theoretic inference of the optimal number of electrodes for future cochlear implants using a spiral cochlea model', 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, pp. 2956-2968. 4 6
2011	Prettejohn, BJ & McDonnell, MD 2011, 'Effect of network topology in opinion formation models', 2nd International Workshop on Collaborative Agents - Research and Development, CARE 2010, Held in Conjunction with the 2010 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT10, Springer Verlag, vol. 6066, pp. 114-124. 3 3
2009	Li, F, McDonnell, MD, Amblard, P-O & Grant, AJ 2009, 'Sensor selection for distributed detection via multiaccess channels', in J Yuan & I Collings (eds), Australian Communications Theory Workshop, IEEE, pp. 77-82. Open access 1
2009	Stocks, N, Nikitin, A, McDonnell, M & Morse, R 2009, 'The role of stochasticity in an information-optimal neural population code', Institute of Physics Publishing, vol. 197, pp. 012-015.
2008	McDonnell, MD 2008, 'Reliable communication and sensing via parallel redundancy in noisy digital receivers', IEEE, pp. 23-28. Open access 5 4
2008	McDonnell, MD 2008, 'Signal compression in biological sensory systems: information theoretic performance limits', BioMEMS and Nanotechnology III, SPIE, vol. 6799, 679913-9. Open access 1
2008	McDonnell, MD, Amblard, P-O & Stocks, NG 2008, 'Stochastic pooling networks: a biologically inspired model for robust signal detection and compression', BICTA 2008, IEEE, pp. 75-82. Open access 1 1

Other outputs

Editorials

M. D. McDonnell, K. Boahen, A. Ijspeert, and T. J. Sejnowski. Engineering intelligent electronic systems based on computational neuroscience. Proceedings of the IEEE, 102:646-651, 2014.

Research

Patents

Details	Registry	Status
System and method for analog to digital conversion Chen, Ying; Pollok, Andre; Haley, David Victor Lawrie; Davis, Linda Mary; McDonnell, Mark Damian	United States	Granted

External engagement & recognition

Collaborations

Highlights

2013 Invited to Chief-guest-edit special issue of Proceedings of the IEEE (published 2014).
2012 Bernstein Lecture invitation, Bernstein Centre for Computation Neuroscience, Munich,Germany (presented October 2012).
2012 Endeavour Research Fellowship, awarded by the Australian Government, Departmentof Education, Employment and Workplace Relations, for a six month research visit to Canada.
2008 South Australian Young Tall Poppy Science Award, sponsored by the Australian Instituteof Political Science, acknowledging outstanding scholarship and research and communityengagement in the understanding and promotion of science.

External engagement & recognition

Collaborations

Organisation	Country
Aalto University	FINLAND
Aston University	UNITED KINGDOM
Australian Defence Force	AUSTRALIA
Australian National University	AUSTRALIA
CNRS, Department of Images and Signals	FRANCE
Consilium Technology	AUSTRALIA
Defence Science and Technology Group	AUSTRALIA
Defence Science and Technology Organisation	AUSTRALIA
Department of Defence	AUSTRALIA
Ecole Normale Suprieure	FRANCE
Ecole Polytechnique Federale de Lausanne	ITALY
Frankfurt Institute for Advanced Studies	GERMANY
GIPSA-lab, Department of Images and Signals	FRANCE
Howard Hughes Medical Institute	UNITED STATES
Humboldt University Berlin	GERMANY
Institute of Statistical Mathematics	JAPAN
Islamic Azad University	IRAN
Macquarie University	AUSTRALIA
Mahasarakham University	THAILAND
Max Planck Institute for Mathematics in the Sciences	GERMANY
Monash University	AUSTRALIA
Myriota	AUSTRALIA
Neuroscience Research Australia	AUSTRALIA
Nicta	AUSTRALIA
Northwestern Polytechnical University	CHINA
Ohio State University	UNITED STATES
Planetary Science Institute	AUSTRALIA
Private Individual	AUSTRALIA
Qingdao University	CHINA
Queen's University Belfast	UNITED KINGDOM
Royal Adelaide Hospital	AUSTRALIA
Stanford University	UNITED STATES
Tubingen University Hospital	GERMANY
Universidad Nacional de Chimborazo	ECUADOR
University of Adelaide	AUSTRALIA
University Of Angers	FRANCE
University of British Columbia	CANADA
University of California	UNITED STATES
University of Colorado at Boulder	UNITED STATES
University of Melbourne	AUSTRALIA
University of Oxford	UNITED KINGDOM
University of Science, Malaysia	MALAYSIA
University of South Australia	AUSTRALIA
University of Stirling	UNITED KINGDOM
University of Sydney	AUSTRALIA
University of Warwick	UNITED KINGDOM
University of Wollongong	AUSTRALIA
Western Sydney University	AUSTRALIA

External engagement & recognition

Engagement/recognition	Year
Visiting Professor University of California San Diego	2017
Affiliate Member Centre of Excellence, Australian Research Council (ARC)	2015
Invited speaker 22nd IEEE International Conference on Telecommunications (ICT), Sydney	2015
Endeavour Research Fellowship Department of Education, Employment and Workplace Relations, Australian Government	2012
Visiting Professor University of British Columbia, Canada.	2012
Australian Research Fellowship Australian Research Council (ARC)	2010

Other

A/Prof. McDonnell enjoys translating cutting-edge machine learning methods to solutions for end-user partners across many industry and service sectors.

Current partners include:

Alcidion corporation (health sector)
MyBudget (financial services)
Sage Automation (advanced manufacturing)
Consilium Technology (IT)
DST Group (defence)

Teaching & student supervision

Research degree supervision

Supervisions from 2010 shown

Thesis title	Student status
End-to-End deep neural network based speech recognition incorporating speech enhancement	Current
Analysis and spiking implementation of the hierarchical temporal memory model for pattern and sequence recognition	Completed
Artificial intelligence and brain cancer survival rate based on tumour microenvironment characteristics	Completed
Computational models of stochastic variability in the auditory nerve and electromyography recordings induced by transcranial magnetic stimulation	Completed
Efficient modular training methods for deep or wide neural networks using Extreme Learning Machines	Completed
Machine learning for predictive modelling and risk factor discovery in health and wealth	Completed
Mechanisms of learning in the piriform cortex	Completed
Modeling of cognitive function during audio distracted driving using EEG	Completed
The application of value based reinforcement learning in the presence of uncertainty: progress towards trustworthy autonomy	Completed
Theoretical models of information transmission at the electro-neural interface of cochlear implants	Completed
Understanding the underlying similarities shared by complex systems: a study of consensus formation, and neuronal network dynamics, through the application of complex network simulations	Completed

more less

Associate Professor Mark D. McDonnell

About me

About me

UniSA STEM

About me

Professional Associations

Experience

Qualifications

Work history

Research

Highlights

Projects

Outputs

Highlights

Books

Chapters

Journal Articles

Conferences

Other outputs

Current research & highlights

Patents

External engagement & recognition

Collaborations

Highlights

Collaborations

External engagement & recognition

Visiting Professor

Affiliate Member

Invited speaker

Endeavour Research Fellowship

Visiting Professor

Australian Research Fellowship

Other

Teaching & student supervision

Courses and programs

Research degree supervision

Gallery