Personal profile
Research Interests
I am a marine image analyst leading in this field at SAMS, with over four years’ experience in biological image analysis. I have previously worked at Cancer Research UK’s Beatson Institute developing custom image analysis pipelines, including deep learning methods with CNNs. I am currently leading the image analysis component of three projects, involving the latest techniques, such as custom deep learning pipelines for the automatic recognition of flora and fauna and photogrammetry/3D modelling.
Prior to working as an image analyst, I completed two Postdocs in advanced Transmission Electron Microscopy, which included developing new energy materials, and a PhD in semiconductor physics.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being -
SDG 14 Life Below Water
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Collaborations from the last five years
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The Potential of Low-Tech Tools and Artificial Intelligence for Monitoring Blue Carbon in Greenland’s Deep Sea
Bax, N., Halpin, J., Long, S., Yesson, C., Marlow, J. & Zwerschke, N., 1 Jan 2025, In: Oceanography. 38, 1, p. 89-91 3 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile318 Downloads (Pure) -
3D photogrammetry and deep-learning deliver accurate estimates of epibenthic biomass
Marlow, J., Halpin, J. E. & Wilding, T. A., 26 Mar 2024, In: Methods in Ecology and Evolution.Research output: Contribution to journal › Article › peer-review
Open AccessFile7 Citations (Scopus)140 Downloads (Pure) -
Detection and characterisation of derelict creel fleets to evaluate marine megafauna entanglement risk in Scottish waters: CreelMap Final Project Report Scottish Marine Environmental Enhancement Fund (SMEEF) projects 502257 / 502492
Benjamins, S., Fox, C., Marlow, J., Halpin, J., Rybanska , P. & Howe, J., 9 Oct 2024, 32 p.Research output: Book/Report › Other report
Open AccessFile167 Downloads (Pure) -
A Correlative Study of Interfacial Segregation in a Cu-Doped TiNiSn Thermoelectric half-Heusler Alloy
Halpin, J. E., Jenkins, B., Moody, M. P., Webster, R. W. H., Bos, J. W. G., Bagot, P. A. J. & Maclaren, D. A., 23 Aug 2022, In: ACS Applied Electronic Materials. 4, 9, p. 4446-4454 9 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile5 Citations (Scopus)67 Downloads (Pure) -
Human-correlated genetic HCC models identify combination therapy for precision medicine
Müller, M., May, S., Hall, H., Kendall, T. J., McGarry, L., Blukacz, L., Nuciforo, S., Jamieson, T., Phinichkusolchit, N., Dhayade, S., Leslie, J., Sprangers, J., Malviya, G., Mrowinska, A., Johnson, E., McCain, M., Halpin, J., Kiourtis, C., Georgakopoulou, A. & Nixon, C. & 16 others, , 12 May 2022, (Submitted) 59 p.Research output: Working paper › Preprint
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Atom Probe Tomography of a Cu-Doped TiNiSn Thermoelectric Material: Nanoscale Structure and Optimization of Analysis Conditions
He, H., Halpin, J. E., Popuri, S. R., Daly, L., Bos, J. W. G., Moody, M. P., Maclaren, D. A. & Bagot, P. A. J., 28 Jul 2021, In: Microscopy and Microanalysis. 28, 4, p. 1340-1347 8 p.Research output: Contribution to journal › Article › peer-review
6 Citations (Scopus) -
Multiple scattering in scanning helium microscopy
Lambrick, S. M., Vozdecký, L., Bergin, M., Halpin, J. E., Maclaren, D. A., Dastoor, P. C., Przyborski, S. A., Jardine, A. P. & Ward, D. J., 10 Feb 2020, In: Applied Physics Letters. 116, 6, 061601.Research output: Contribution to journal › Article › peer-review
13 Citations (Scopus)
Datasets
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3D Photogrammetry and deep-learning deliver accurate estimates of epibenthic biomass
Marlow, J. (Creator), Halpin, J. (Creator) & Wilding, T. (Creator), 6 Mar 2024
DOI: 10.5061/dryad.1rn8pk11z, https://pureadmin.uhi.ac.uk/admin/files/50149348/Methods_Ecol_Evol_-_2024_-_Marlow_-_3D_photogrammetry_and_deep_learning_deliver_accurate_estimates_of_epibenthic_biomass.pdf
Dataset