Zygmunt Szpak
Australian Institute for Machine Learning
Division of Research and Innovation
I'm a computer scientist and senior research associate in the School of Computer Science at the University of Adelaide, South Australia. I work in the Australian Institute for Machine Learning on numerous industry-inspired computer vision and machine learning problems.
When I am not engaged in a concrete industry project, my primary research endeavours are devoted to problems in projective parameter estimation, in the context of multiple-view geometry. The statistical estimation problems that I am interested in fall under the banner of non-linear errors-in-variables models.
You can find out more about my research themes here: https://zygmuntszpak.github.io/
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Appointments
Date Position Institution name 2013 - ongoing Senior Research Associate The University of Adelaide -
Language Competencies
Language Competency Afrikaans Can speak English Can read, write, speak and peer review German Can read, write, speak and peer review Polish Can read and speak -
Education
Date Institution name Country Title The University of Adelaide Australia PhD Computer Science The University of KwaZulu-Natal South Africa MSc Computer Science (Cum Laude) The University of KwaZulu-Natal South Africa Bachelor of Science Honours Computer Science (Summa Cum Laude) -
Research Interests
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Journals
Year Citation 2023 Cebulla, A., Szpak, Z., & Knight, G. (2023). Preparing to work with artificial intelligence: assessing WHS when using AI in the workplace. International Journal of Workplace Health Management, 16(4), 294-312.
Scopus142022 Cebulla, A., Szpak, Z., Howell, C., Knight, G., & Hussain, S. (2022). Applying ethics to AI in the workplace: the design of a scorecard for Australian workplace health and safety.. AI Soc, 38(2), 919-935.
Scopus19 WoS42021 Kuang, B., Pena, G., Szpak, Z., Edwards, S., Battersby, R., Cowled, P., . . . Fitridge, R. (2021). Assessment of a smartphone-based application for diabetic foot ulcer measurement.. Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society, 29(3), 6 pages.
Scopus15 WoS7 Europe PMC62020 Pena, G., Kuang, B., Szpak, Z., Cowled, P., Dawson, J., & Fitridge, R. (2020). Evaluation of a Novel Three-Dimensional Wound Measurement Device for Assessment of Diabetic Foot Ulcers. ADVANCES IN WOUND CARE, 9(11), 9 pages.
Scopus17 WoS8 Europe PMC52020 Chojnacki, W., Szpak, Z. L., & Wadenbäck, M. (2020). The equivalence of two definitions of compatible homography matrices. Pattern Recognition Letters, 135, 38-43.
Scopus2 WoS12019 Chojnacki, W., & Szpak, Z. L. (2019). Determining ellipses from low-resolution images with a comprehensive image formation model. Journal of the Optical Society of America A, 36(2), 212-233.
2015 Chojnacki, W., Szpak, Z., Brooks, M., & van Den Hengel, A. (2015). Enforcing consistency constraints in uncalibrated multiple homography estimation using latent variables. Machine Vision and Applications, 26(2-3), 401-422.
Scopus5 WoS42015 Szpak, Z., Chojnacki, W., & van den Hengel, A. (2015). Guaranteed ellipse fitting with a confidence region and an uncertainty measure for centre, axes, and orientation. Journal of Mathematical Imaging and Vision, 52(2), 173-199.
Scopus40 WoS322014 Szpak, Z., Chojnacki, W., Eriksson, A., & van den Hengel, A. (2014). Sampson distance based joint estimation of multiple homographies with uncalibrated cameras. Computer Vision and Image Understanding, 125, 200-213.
Scopus20 WoS172011 Szpak, Z., & Tapamo, J. (2011). Maritime surveillance: Tracking ships inside a dynamic background using a fast level-set. Expert Systems with Applications, 38(6), 6669-6680.
Scopus79 WoS582008 Szpak, Z. L., & Tapamo, J. -R. (2008). Automatic and interactive retinal vessel segmentation.. South Afr. Comput. J., 40, 23-30. -
Book Chapters
Year Citation 2023 Cebulla, A., & Szpak, Z. (2023). Workplace Relations with AI in Mind: What Is Likely to Change?. In The Future of Work and Technology: Global Trends, Challenges and Policies with an Australian Perspective (pp. 151-172). Chapman and Hall/CRC.
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Conference Papers
Z. Szpak, W. Chojnacki “Target Recognition and Measurement at the Limits of Resolution”, AUD 100k Defence Science Technology Organisation, 2017
Z. Szpak, W. Chojnacki “Parameter Estimation at the Limits of Resolution”, AUD 78k Defence Science Technology Organisation, 2016
Z. Szpak, J. Mackenzie “Sharing the knowledge required to successfully utilise object detection software for use in future research opportunities”, AUD 20k ECMS Faculty, Adelaide University, 2016
Connect With Me
External Profiles