Staff profile

I am an Assistant Professor in the Department of Computer Science at Durham University. My research interests are computational and mathematical intelligence, non-linear analysis and computing, and the applications in biomedical and physical sciences. I am actively seeking collaborative opportunities motivated by industrial practices and theoretical principles across disciplines.

• Medical Image Analysis
• Computer Vision
• Machine Learning
• Artificial Intelligence

Conference Paper

• Hu, Y., Ren, H., Hu, C., Deng, J., & Xie, X. (2023). An Element-Wise Weights Aggregation Method for Federated Learning. In 2023 IEEE International Conference on Data Mining Workshops (ICDMW). https://doi.org/10.1109/icdmw60847.2023.00031
• Kenning, M. P., Deng, J., Edwards, M., & Xie, X. (2021). Locating Datacenter Link Faults with a Directed Graph Convolutional Neural Network. . https://doi.org/10.5220/0010301403120320
• Nagoor, O. H., Whittle, J., Deng, J., Mora, B., & Jones, M. W. (2021). MedZip: 3D medical images lossless compressor using recurrent neural network (LSTM). . https://doi.org/10.1109/icpr48806.2021.9413341
• Nagoor, O. H., Whittle, J., Deng, J., Mora, B., & Jones, M. W. (2020). Lossless compression for volumetric medical images using deep neural network with local sampling. . https://doi.org/10.1109/icip40778.2020.9191031
• Alqahtani, A., Xie, X., Deng, J., & Jones, M. W. (2019). Learning discriminatory deep clustering models. . https://doi.org/10.1007/978-3-030-29888-3_18
• Kenning, M. P., Xie, X., Edwards, M., & Deng, J. (2018). Local representation learning with a convolutional autoencoder. . https://doi.org/10.1109/icip.2018.8451233
• Tsang, G., Deng, J., & Xie, X. (2018). Recurrent neural networks for financial time-series modelling. . https://doi.org/10.1109/icpr.2018.8545666
• Alqahtani, A., Xie, X., Deng, J., & Jones, M. W. (2018). A deep convolutional auto-encoder with embedded clustering. . https://doi.org/10.1109/icip.2018.8451506
• Ravenscroft, D., Deng, J., Xie, X., Terry, L., Margrain, T. H., North, R. V., & Wood, A. (2017). Amd classification in choroidal oct using hierarchical texton mining. . https://doi.org/10.1007/978-3-319-70353-4_21
• Deng, J., & Xie, X. (2017). Nested shallow cnn-cascade for face detection in the wild. . https://doi.org/10.1109/fg.2017.29
• Edwards, M., Deng, J., & Xie, X. (2017). Labeling subtle conversational interactions within the CONVERSE dataset. . https://doi.org/10.1109/percomw.2017.7917547
• Ravenscroft, D., Deng, J., Xie, X., Terry, L., Margrain, T. H., North, R. V., & Wood, A. (2017). Learning feature extractors for AMD classification in OCT using convolutional neural networks. . https://doi.org/10.23919/eusipco.2017.8081167
• Deng, J., & Xie, X. (2017). Detect face in the wild using CNN cascade with feature aggregation at multi-resolution. . https://doi.org/10.1109/icip.2017.8297067
• Deng, J., Xie, X., & Edwards, M. (2016). Combining stacked denoising autoencoders and random forests for face detection. . https://doi.org/10.1007/978-3-319-48680-2_31
• Deng, J., Xie, X., Terry, L., Wood, A., White, N., Margrain, T. H., & North, R. V. (2016). Age-related macular degeneration detection and stage classification using choroidal oct images. . https://doi.org/10.1007/978-3-319-41501-7_79
• Lacey, A., Deng, J., & Xie, X. (2014). Protein classification using Hidden Markov models and randomised decision trees. . https://doi.org/10.1109/bmei.2014.7002856
• Deng, J., Xie, X., Alcock, R., & Roobottom, C. (2014). 3D interactive coronary artery segmentation using random forests and Markov random field optimization. . https://doi.org/10.1109/icip.2014.7025189
• Deng, J., Xie, X., & Zhou, S. (2014). Conversational interaction recognition based on bodily and facial movement. . https://doi.org/10.1007/978-3-319-11758-4_26
• Deng, J., Xie, X., Daubney, B., Fang, H., & Grant, P. W. (2013). Recognizing conversational interaction based on 3D human pose. . https://doi.org/10.1007/978-3-319-02895-8_13
• Fang, H., Deng, J., Xie, X., & Grant, P. W. (2013). From clamped local shape models to global shape model. . https://doi.org/10.1109/icip.2013.6738725

Doctoral Thesis

• Deng, J. (2017). Adaptive Learning for Segmentation and Detection. (Thesis). Swansea University. Retrieved from https://durham-repository.worktribe.com/output/1647119

Journal Article

• Xie, X., Hu, C., Ren, H., & Deng, J. (2024). A survey on vulnerability of federated learning: A learning algorithm perspective. Neurocomputing, 573, Article 127225. https://doi.org/10.1016/j.neucom.2023.127225
• Ren, H., Deng, J., Xie, X., Ma, X., & Wang, Y. (2024). FedBoosting: Federated learning with gradient protected boosting for text recognition. Neurocomputing, 569, Article 127126. https://doi.org/10.1016/j.neucom.2023.127126
• Cai, Z., Xie, X., Deng, J., Dou, Z., Tong, B., & Ma, X. (2023). Image restoration with group sparse representation and low‐rank group residual learning. IET Image Processing, https://doi.org/10.1049/ipr2.12982
• Ren, H., Deng, J., & Xie, X. (2022). GRNN: generative regression neural network—a data leakage attack for federated learning. https://doi.org/10.1145/3510032
• Ma, X., Tan, S., Xie, X., Zhong, X., & Deng, J. (2022). Joint multi-label learning and feature extraction for temporal link prediction. Pattern Recognition, 121, https://doi.org/10.1016/j.patcog.2021.108216
• Kenning, M., Deng, J., Edwards, M., & Xie, X. (2022). A directed graph convolutional neural network for edge-structured signals in link-fault detection. Pattern Recognition Letters, 153, 100-106. https://doi.org/10.1016/j.patrec.2021.12.003
• Nagoor, O. H., Whittle, J., Deng, J., Mora, B., & Jones, M. W. (2022). Sampling strategies for learning-based 3D medical image compression. https://doi.org/10.1016/j.mlwa.2022.100273
• Deng, J., & Xie, X. (2021). 3D Interactive Segmentation With Semi-Implicit Representation and Active Learning. IEEE Transactions on Image Processing, 30, 9402-9417. https://doi.org/10.1109/tip.2021.3125491
• Wang, Y., Xia, Z., Deng, J., Xie, X., Gong, M., & Ma, X. (2021). TLGP: a flexible transfer learning algorithm for gene prioritization based on heterogeneous source domain. BMC Bioinformatics, 22(9), 1-15. https://doi.org/10.1186/s12859-021-04190-9
• Boileau, E., Pant, S., Roobottom, C., Sazonov, I., Deng, J., Xie, X., & Nithiarasu, P. (2018). Estimating the accuracy of a reduced-order model for the calculation of fractional flow reserve (FFR). International Journal for Numerical Methods in Biomedical Engineering, 34(1), https://doi.org/10.1002/cnm.2908
• Daubney, B., Xie, X., Deng, J., Mac Parthaláin, N., & Zwiggelaar, R. (2016). Fixing the root node: Efficient tracking and detection of 3D human pose through local solutions. Image and Vision Computing, 52, 73-87. https://doi.org/10.1016/j.imavis.2016.05.010
• Edwards, M., Deng, J., & Xie, X. (2016). From pose to activity: Surveying datasets and introducing CONVERSE. Computer Vision and Image Understanding, 144, 73-105. https://doi.org/10.1016/j.cviu.2015.10.010
• Deng, J., Xie, X., & Daubney, B. (2014). A bag of words approach to subject specific 3D human pose interaction classification with random decision forests. Graphical Models, 76(3), 162-171. https://doi.org/10.1016/j.gmod.2013.10.006