Related Publications

Responsible AI theories and algorithms

• Lin, A., Lu, J., Xuan, J., Zhu, F., & Zhang, G. (2020). A causal Dirichlet mixture model for causal inference from observational data. ACM Transactions on Intelligent Systems and Technology, 11(3), 1-29.

• Fang, Z., Lu, J., Liu, F., Xuan, J. & Zhang, G. (2020) ‘Open set domain adaptation: Theoretical bound and algorithm’, IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 10, pp. 4309–4322.

• Lu, J., Zuo, H., & Zhang, G. (2019). Fuzzy multiple-source transfer learning. IEEE Transactions on Fuzzy Systems, 28(12), 3418-3431. 

Sustainable Grain

• Li, C. (co-author), Avni, R. et al. (2025) A pangenome and pantranscriptome of hexaploid oat. Nature.

• Jayakodi, M., Padmarasu, S., Haberer, G., Bonthala, V. S., Gundlach, H., Monat, C., Lux, T., Kamal, N., Lang, D., Himmelbach, A., Ens, J., Zhang, X.-Q., Angessa, T. T., Zhou, G., Tan, C., Hill, C., Wang, P., Schreiber, M., Boston, L. B., Plott, C., Jenkins, J., Guo, Y., Fiebig, A., Budak, H., Xu, D., Zhang, J., Wang, C., Grimwood, J., Schmutz, J., Guo, G., Zhang, G., Mochida, K., Hirayama, T., Sato, K., Chalmers, K. J., Langridge, P., Waugh, R., Pozniak, C. J., Scholz, U. & Mayer, K. F. X. (2020) ‘The barley pan-genome reveals the hidden legacy of mutation breeding’, Nature.

• Karunarathne, S. D., Han, Y., Zhang, X.-Q. & Li, C. (2022) ‘CRISPR/Cas9 gene editing and natural variation analysis demonstrate the potential for HvARE1 in improvement of nitrogen use efficiency in barley’, Journal of Integrative Plant Biology, vol. 64, no. 3, pp. 756–770.

• Hu, H., Wang, P., Angessa, T. T., Zhang, X.-Q., Chalmers, K. J., Zhou, G., Hill, C. B., Jia, Y., Simpson, C., Fuller, J., Saxena, A., Al Shamaileh, H., Iqbal, M., Chapman, B., Kaur, P., Dudchenko, O., Lieberman Aiden, E., Keeble-Gagnere, G., Westcott, S., Leah, D., Tibbits, J. F., Waugh, R., Langridge, P., Varshney, R., He, T. & Li, C. (2023) ‘Genomic signatures of barley breeding for environmental adaptation to the new continents’, Plant Biotechnology Journal, vol. 21, no. 9, pp. 1719–1721. doi:10.1111/pbi.14077.

 Sensing

• Yang, Z., Cole, K. L. H., Qiu, Y., Somorjai, I. M. L., Wijesinghe, P., Nylk, J., Cochran, S., Spalding, G. C., Lyons, D. A. & Dholakia, K. (2019) ‘Light sheet microscopy with acoustic sample confinement’, Nature Communications, vol. 10, no. 1. doi:10.1038/s41467-019-08514-5.

• Vettenburg, T., Dalgarno, H. I. C., Nylk, J., Coll-Lladó, C., Ferrier, D. E. K., Čižmár, T., Gunn-Moore, F. J. & Dholakia, K. (2014) ‘Lightsheet microscopy using an Airy beam’, Nature Methods, vol. 11, no. 5, pp. 541–544. doi:10.1038/nmeth.2922.

• Arita, Y., Mazilu, M. & Dholakia, K. (2013) ‘Laser-induced rotation and cooling of a trapped microgyroscope in vacuum’, Nature Communications, vol. 4, no. 1. doi:10.1038/ncomms3374.

Agronomy

• Murphy, D., Leopold, M., van Gool, D., Hoyle, F. & Stockdale, E. (2017) ‘Soil quality: 1 Constraints to plant production’, SoilsWest, vol. 1, no. 1, Murdoch University, Perth.

• Vuong, P., Lim, D. J., Murphy, D. V., Wise, M. J., Whiteley, A. S. & Kaur, P. (2021) ‘Developing bioprospecting strategies for bioplastics through the large-scale mining of microbial genomes’, Frontiers in Microbiology, vol. 12. doi:10.3389/fmicb.2021.697309.

• Mathes, F., Murugaraj, P., Bougoure, J., Pham, V. T. H., Truong, V. K., Seufert, M., Wissemeier, A. H., Mainwaring, D. E. & Murphy, D. V. (2020) ‘Engineering rhizobacterial community resilience with mannose nanofibril hydrogels towards maintaining grain production under drying climate stress’, Soil Biology & Biochemistry, vol. 142. doi:10.1016/j.soilbio.2020.107715.

Digital Carbon

• Alghanmi, N. A., Alghanmi, N., Alhosaini, H. & Hussain, F. K. (2023) ‘Carbon credits storage: A comparative multifactor analysis of on-chain vs off-chain approaches’, 2023 IEEE International Conference on e-Business Engineering (ICEBE), pp. 134–142. doi:10.1109/icebe59045.2023.00031.

• Azadi, M., Emrouznejad, A., Ramezani, F. & Hussain, F. K. (2022) ‘Efficiency measurement of cloud service providers using network data envelopment analysis’, IEEE Transactions on Cloud Computing, vol. 10, no. 1, pp. 348–355. doi:10.1109/tcc.2019.2927340.

• Alhadrami, Y. (2020) ‘Real time dataset generation framework for intrusion detection systems in IoT’, Future Generation Computer Systems, vol. 108, pp. 414–423. doi:10.1016/j.future.2020.02.051.