Hello! I'm a software engineer, astrophysicist, and former Earth observation data scientist. I like data and I'm passionate about good quality, robust, reliable, and reproducible software. I'm interested in applications of machine learning to wide-area surveys, both in the sky and on the ground.
I used to be part of the Research School of Astronomy at the Australian National University, and the Foundations and Methods of Machine Learning group at Data61/CSIRO. I was also part of Radio Galaxy Zoo, a citizen science project which aimed to put eyes on a huge amount of the radio sky.
This site is a bit of a work in progress, but so is everything, so that's okay.
https://orcid.org/0000-0001-5110-8845
Alger, M. (2021). Learning to Identify Extragalactic Radio Sources. The Australian National University. https://doi.org/10.25911/51KP-JX25
Alger, M. J., Banfield, J. K., Ong, C. S., Rudnick, L., Wong, O. I., Wolf, C., Andernach, H., Norris, R. P., & Shabala, S. S. (2018). Radio Galaxy Zoo: machine learning for radio source host galaxy cross-identification. Monthly Notices of the Royal Astronomical Society, 478(4), 5556–5572. https://doi.org/10.1093/mnras/sty1308
Alger, M. J., Livingston, J. D., McClure-Griffiths, N. M., Nabaglo, J. L., Wong, O. I., & Ong, C. S. (2021). Interpretable Faraday complexity classification. Publications of the Astronomical Society of Australia, 38. https://doi.org/10.1017/pasa.2021.10
Chen, D., Kerai, V., Alger, M. J., Wong, O. I., & Ong, C. S. (2023). Radio Galaxy Zoo: Tagging radio subjects using text. Publications of the Astronomical Society of Australia, 40. https://doi.org/10.1017/pasa.2023.50
Dunn, B., Ai, E., Alger, M. J., Fanson, B., Fickas, K. C., Krause, C. E., Lymburner, L., Nanson, R., Papas, P., Ronan, M., & Thomas, R. F. (2023). Wetlands Insight Tool: Characterising the Surface Water and Vegetation Cover Dynamics of Individual Wetlands Using Multidecadal Landsat Satellite Data. Wetlands, 43(4). https://doi.org/10.1007/s13157-023-01682-7
Galvin, T. J., Huynh, M., Norris, R. P., Wang, X. R., Hopkins, E., Wong, O. I., Shabala, S., Rudnick, L., Alger, M. J., & Polsterer, K. L. (2019). Radio Galaxy Zoo: Knowledge Transfer Using Rotationally Invariant Self-organizing Maps. Publications of the Astronomical Society of the Pacific, 131(1004), 108009. https://doi.org/10.1088/1538-3873/ab150b
Krause, C., Dunn, B., Bishop-Taylor, R., Adams, C., Burton, C., Alger, M., Chua, S., Phillips, C., Newey, V., Kouzoubov, K., Leith, A., Ayers, D., Hicks, A., & contributors, D. N. (2021). Digital Earth Australia notebooks and tools repository. Commonwealth of Australia (Geoscience Australia). https://doi.org/10.26186/145234
Krause, C. E., Newey, V., Alger, M. J., & Lymburner, L. (2021). Mapping and Monitoring the Multi-Decadal Dynamics of Australia’s Open Waterbodies Using Landsat. Remote Sensing, 13(8), 1437. https://doi.org/10.3390/rs13081437
Livingston, J. D., McClure-Griffiths, N. M., Gaensler, B. M., Seta, A., & Alger, M. J. (2021). Heightened Faraday complexity in the inner 1~0.167 kpc of the galactic centre. Monthly Notices of the Royal Astronomical Society, 502(3), 3814–3828. https://doi.org/10.1093/mnras/stab253
Ralph, N. O., Norris, R. P., Fang, G., Park, L. A. F., Galvin, T. J., Alger, M. J., Andernach, H., Lintott, C., Rudnick, L., Shabala, S., & Wong, O. I. (2019). Radio Galaxy Zoo: Unsupervised Clustering of Convolutionally Auto-encoded Radio-astronomical Images. Publications of the Astronomical Society of the Pacific, 131(1004), 108011. https://doi.org/10.1088/1538-3873/ab213d
Wong, O. I., Garon, A. F., Alger, M. J., Rudnick, L., Shabala, S. S., Willett, K. W., Banfield, J. K., Andernach, H., Norris, R. P., Swan, J., Hardcastle, M. J., Lintott, C. J., White, S. V., Seymour, N., Kapińska, A. D., Tang, H., Simmons, B. D., & Schawinski, K. (2024). Radio Galaxy Zoo data release 1: 100185 radio source classifications from the FIRST and ATLAS surveys. Monthly Notices of the Royal Astronomical Society, 536(4), 3488–3506. https://doi.org/10.1093/mnras/stae2790
Wu, C., Wong, O. I., Rudnick, L., Shabala, S. S., Alger, M. J., Banfield, J. K., Ong, C. S., White, S. V., Garon, A. F., Norris, R. P., Andernach, H., Tate, J., Lukic, V., Tang, H., Schawinski, K., & Diakogiannis, F. I. (2018). Radio Galaxy Zoo: ClaRAN — a deep learning classifier for radio morphologies. Monthly Notices of the Royal Astronomical Society. https://doi.org/10.1093/mnras/sty2646