| 2020 | ICASSP | Acoustic Scene Classification Using Deep Residual Networks with Late Fusion of Separated High and Low Frequency Paths. | Mark D. McDonnell, Wei Gao |
| 2020 | IJCNN | End-to-End Phoneme Recognition using Models from Semantic Image Segmentation. | Wei Gao, Ahmad Hashemi-Sakhtsari, Mark D. McDonnell |
| 2019 | DICTA | Using Style-Transfer to Understand Material Classification for Robotic Sorting of Recycled Beverage Containers. | Mark D. McDonnell, Bahar Moezzi, Russell S. A. Brinkworth |
| 2019 | ICDAR | Thai Handwritten Recognition on Text Block-Based from Thai Archive Manuscripts. | Rapeeporn Chamchong, Wei Gao, Mark D. McDonnell |
| 2018 | DICTA | Diagnosing Convolutional Neural Networks using Their Spectral Response. | Victor Stamatescu, Mark D. McDonnell |
| 2018 | ICLR | Training wide residual networks for deployment using a single bit for each weight. | Mark D. McDonnell |
| 2018 | IJCNN | A model of neurobiologically plausible least-squares learning in visual cortex. | Samya Bagchi, Mark D. McDonnell |
| 2017 | ICONIP | Analysis of Gradient Degradation and Feature Map Quality in Deep All-Convolutional Neural Networks Compared to Deep Residual Networks. | Wei Gao, Mark D. McDonnell |
| 2017 | ICONIP | Fast, Automatic and Scalable Learning to Detect Android Malware. | Mahmood Yousefi-Azar, Len Hamey, Vijay Varadharajan, Mark D. McDonnell |
| 2017 | IJCNN | Regularized training of the extreme learning machine using the conjugate gradient method. | Philip de Chazal, Mark D. McDonnell |
| 2017 | IJCNN | Semi-supervised convolutional extreme learning machine. | Mahmood Yousefi-Azar, Mark D. McDonnell |
| 2016 | DICTA | Understanding Data Augmentation for Classification: When to Warp? | Sebastien C. Wong, Adam Gatt, Victor Stamatescu, Mark D. McDonnell |
| 2016 | IJCNN | Efficient computation of the Levenberg-Marquardt algorithm for feedforward networks with linear outputs. | Philip de Chazal, Mark D. McDonnell |
| 2016 | IJCNN | On the importance of pair-wise feature correlations for image classification. | Mark D. McDonnell, Robby G. McKilliam, Philip de Chazal |
| 2016 | IJCNN | Integrating convolutional neural networks into a sparse distributed representation model based on mammalian cortical learning. | Daniel E. Padilla, Mark D. McDonnell |
| 2016 | IJCNN | Enhancing deep extreme learning machines by error backpropagation. | Migel D. Tissera, Mark D. McDonnell |
| 2016 | IJCNN | Modular expansion of the hidden layer in Single Layer Feedforward neural Networks. | Migel D. Tissera, Mark D. McDonnell |
| 2015 | IJCNN | Enhanced image classification with a fast-learning shallow convolutional neural network. | Mark D. McDonnell, Tony Vladusich |
| 2014 | INFOCOM | Distance distributions for real cellular networks. | Siyi Wang, Weisi Guo, Mark D. McDonnell |
| 2014 | INFOCOM | Transmit pulse shaping for molecular communications. | Siyi Wang, Weisi Guo, Mark D. McDonnell |
| 2014 | ISIT | Using convex optimization to compute channel capacity in a channel model of cochlear implant stimulation. | Xiao Gao, David B. Grayden, Mark D. McDonnell |
| 2014 | ITW | Inferring the dynamic range of electrode current by using an information theoretic model of cochlear implant stimulation. | Xiao Gao, David B. Grayden, Mark D. McDonnell |
| 2004 | ICASSP | Signal reconstruction via noise through a system of parallel threshold nonlinearities. | Mark D. McDonnell, Derek Abbott |
| 2004 | ISIT | Optimal quantization in neural coding. | Mark D. McDonnell, Derek Abbott |