Publications

Below you can find a list of publications resulting from projects we have worked on.

• Wilson, T., Wisdish, S., Osofa, J., & Farris, D. J. (2025). Evaluating Machine Learning-Based Classification of Human Locomotor Activities for Exoskeleton Control Using Inertial Measurement Unit and Pressure Insole Data. Sensors, 25(17), 5365. https://doi.org/10.3390/s25175365.
• Sergeev, D.E., Boutle, I.A., Lambert, F.H., Mayne, N.J., Bendall, T., Kohary, K., Olivier, R., Shipway, B., 2024, The impact of the explicit representation of convection on the climate of a tidally locked planet in global stretched-mesh simulations. Preprint arXiv:2402.19277.
• O'Shea-Wheller, T.A., Corbett, A., Osborne, J.L. et al. VespAI: a deep learning-based system for the detection of invasive hornets. Commun Biol 7, 354 (2024). DOI:10.1038/s42003-024-05979-z.
• Sergeev, D. E., Mayne, N. J., Bendall, T., Boutle, I. A., Brown, A., Kavčič, I., Kent, J., Kohary, K., Manners, J., Melvin, T., Olivier, E., Ragta, L. K., Shipway, B., Wakelin, J., Wood, N., and Zerroukat, M.: Simulations of idealised 3D atmospheric flows on terrestrial planets using LFRic-Atmosphere, Geosci. Model Dev., 16, 5601–5626, https://doi.org/10.5194/gmd-16-5601-2023, 2023.
• O. Kyriienko and E.Magnusson (2022). ‘Unsupervised quantum machine learning for fraud detection’. arXiv:2208.01203 [quant-ph]. DOI:10.48550/arXiv.2208.01203.
• Hawes, T., Johns, M., White, H., Salter, J., Olivier, E., Kimpton, L., Xiong, X., & Challenor, P. (2025). EXAUQ-Toolbox (Version v0.3.2) [Computer software]. https://doi.org/10.5281/zenodo.15005642
• Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.: Global Carbon Budget 2022, Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, 2022.