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Personal profile

Research Interests

My research interests are broadly in the areas of machine learning and computer vision. I am particularly interested in questions related to human-in-the-loop machine learning with the aim of creating next-generation methods that take advantage of the complementary strengths of humans and machines. This involves the development of new models and algorithms for interacting with communities of experts to enable solutions for problems such as computer assisted teaching, interpretable representation learning, and applications such as biodiversity monitoring.

Biography

Oisin Mac Aodha received a BEng in Electronic and Computing Engineering from the National University of Ireland Galway in 2007. He then went on to receive an MSc in Machine Learning from the University College of London (UCL) in 2008 and afterwards spent one year as a research assistant at ETH Zurich. He was awarded an NUI Travelling Studentship in the Sciences in 2010 and subsequently obtained a PhD in Computer Science from UCL in 2014 under the supervision of Prof. Gabriel Brostow. After his PhD he was a postdoc at UCL working on interactive machine learning methods for efficient biodiversity monitoring. Between 2016 and 2019 he was a postdoc at the California Institute of Technology working with Prof. Pietro Perona. In 2019 he started as a Lecturer in Machine Learning in the School of Informatics at the University of Edinburgh.

Qualifications

BEng Electronic and Computing Engineering, National University of Ireland Galway, 2003-2007
MSc Machine Learning, University College London, 2007-2008
PhD Computer Science, University College London, 2010-2014

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Collaborations and top research areas from the last five years

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  • Incremental Generalized Category Discovery

    Zhao, B. & Mac Aodha, O., 15 Jan 2024, 2023 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, p. 19080-19090 11 p. (International Conference on Computer Vision (ICCV)).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
  • Active Learning-Based Species Range Estimation

    Lange, C., Cole, E., Van Horn, G. & Mac Aodha, O., 21 Sept 2023, (Accepted/In press) 37th Conference on Neural Information Processing Systems (NeurIPS 2023). PMLR, p. 1-22 22 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
  • Virtual Occlusions Through Implicit Depth

    Watson, J., Sayed, M., Qureshi, Z., Brostow, G. J., Vicente, S., Mac Aodha, O. & Firman, M., 22 Aug 2023, 2023 Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, p. 9053-9064 12 p. (IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
  • Bayesian Optimization for Design of Multiscale Biological Circuits

    Merzbacher, C., Mac Aodha, O. & Oyarzún, D. A., 21 Jul 2023, In: ACS Synthetic Biology. 12, 7, p. 2073-2082 10 p.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    File
  • Spatial Implicit Neural Representations for Global-Scale Species Mapping

    Cole, E., van Horn, G., Lange, C., Shepard, A., Leary, P., Perona, P., Loarie, S. & Mac Aodha, O., 10 Jul 2023, Proceedings of the 40th International Conference on Machine Learning. PMLR, Vol. 202. p. 6320-6342 23 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File