Jordan Ubbens

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  • 2016-Present

    Ph.D. student, University of Saskatchewan

    As a Ph.D. member of the Plant Phenotyping and Imaging Research Center at the University of Saskatchewan, I am interested in the application of deep learning to the problem of image-based plant phenotyping. This work is also related to the simulation and modeling of crop plants, as well as genotype-phenotype association. I wrote and maintain Deep Plant Phenomics. During the summer of 2017, I was a visiting PhD student at the Algorithmic Botany lab at the University of Calgary.

    Publications and Presentations ▾

    Ubbens, J. R. & Stavness, I. Latent space association analysis: towards GWAS directly from images. Presented at Phenome 2019, Tucson, Arizona. February 2019.

    Ubbens, J. R. & Stavness, I. An introduction to deep learning in plant phenotyping without the agonizing pain. Presented at Phenome 2018, Tucson, Arizona. February 2018.

    Ubbens, J. R., Cieslak, M., Prusinkiewicz, P. & Stavness, I. (2018). The use of plant models in deep learning: an application to leaf counting in rosette plants. Plant Methods, 14(1), 6. doi:10.1186/s13007-018-0273-z

    Ubbens, J. R. & Stavness, I. (2017). Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks. Front. Plant Sci. 8:1190. doi:10.3389/fpls.2017.01190

  • 2015-2016


    I worked as a project manager at Shiverware, where I led the Swimlytics project for a year following my M.Sc.

    Publications and Presentations ▾

    Barden, J. M., Gerhard, D. B., Vila, O., Ubbens, J. R. & Park, B. The effect of breathing asymmetry on stroke periodicity in competitive front-crawl swimming. Presented at the Sport Innovation (SPIN) Summit, Richmond, British Columbia. October 2017.

  • 2014-2015

    M.Sc., University of Regina

    As a previous Master's student member of the aRMADILo lab at the University of Regina, my work primarily involved machine learning with audio data. My thesis work was about the application of classical sparse coding to audio information using local image features of the spectrogram.

    Publications and Presentations ▾

    Ubbens, J. R. & Gerhard, D. B. (2016). Information rate for fast time-domain instrument classification. In R. Kronland-Martinet, M. Aramaki & S. Ystad (Eds.), Music, Mind & Embodiment: Volume 9617 of the series Lecture Notes in Computer Science. Springer International Press. 297-308. doi:10.1007/978-3-319-46282-0_19

  • 2009-2013

    B.Sc. (Hons), University of Regina

    As an undergraduate student, I was involved in projects related to scaling treatment protocols in clinical psychology using mobile technology such as phones and tablets.

    Publications and Presentations ▾

    Carleton, R. N., Teale Sapach, M. J. N., Oriet, C., Duranceau, S., Lix, L. M., Thibodeau, M. A., Horswill, S. C., Ubbens, J. R., & Asmundson, G. J. G. (2015). A randomized controlled trial of attention modification for social anxiety disorder. Journal of Anxiety Disorders, 33, 35-44. doi:10.1016/j.janxdis.2015.03.011

    Carleton, R. N., Teale, M. J. N., Horswill, S. C., Oriet, C., Ubbens, J. R., & Asmundson, G. J. G. Attending to the details: A longitudinal RCT of an attention modification program for Social Anxiety Disorder. Presented at the 33rd annual conference of the Anxiety Disorders Association of America, La Jolla, California. April 2013.