Dr Nikodem Rybak
Research Fellow – Machine Learning and Natural Language Processing
MISHC
Publications
Book Chapters
Rybak, Nikodem and Hassall, Maureen (2024). Artificial Intelligence Applications for Workplace Safety : An In-Depth Examination. Encyclopedia of Information Science and Technology. (pp. 1-19) Hershey, PA United States: IGI Global. doi: 10.4018/978-1-6684-7366-5.ch085
Rybak, Nikodem and Hassall, Maureen (2023). Machine learning-enhanced text mining as a support tool for research on climate change : theoretical and technical considerations. 5G, artificial intelligence, and next generation internet of things. (pp. 86-122) edited by Patricia Ordóñez de Pablos and Xi Zhang. Hershey, PA, United States: IGI Global. doi: 10.4018/978-1-6684-8634-4.ch004
Rybak, Nikodem and Hassall, Maureen (2022). Machine learning enhanced decision-making: applications of Industry 4.0. Handbook of smart materials, technologies, and devices. (pp. 477-517) edited by Chaudhery Mustansar Hussain and Paolo Di Sia. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-84205-5_20
Journal Articles
Codoceo-Contreras, Loreto, Rybak, Nikodem and Hassall, Maureen (2024). Exploring the impacts of automation in the mining industry: a systematic review using natural language processing. Mining Technology: Transactions of the Institutions of Mining and Metallurgy, 133 (3), 191-213. doi: 10.1177/25726668241270486
Harker, Callan, Hassall, Maureen, Lant, Paul, Rybak, Nikodem and Dargusch, Paul (2022). What can machine learning teach us about Australian climate risk disclosures?. Sustainability, 14 (16) 10000, 10000. doi: 10.3390/su141610000
Rybak, Nikodem and Angus, Daniel J. (2021). Tracking conflict and emotions with a computational qualitative discourse analytic support approach. PLoS ONE, 16 (5 May) e0251186, 1-29. doi: 10.1371/journal.pone.0251186
Conference Papers
Rybak, Nikodem and Hassall, Maureen (2021). Deep learning unsupervised text-based detection of anomalies in U.S. Chemical Safety and Hazard Investigation Board reports. International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), Mauritius, Mauritius, 7-8 October 2021. Piscataway, NJ United States: IEEE. doi: 10.1109/iceccme52200.2021.9590834
Rybak, Nikodem, Hassall, Maureen, Parsa, Kourosh and Angus, Daniel J. (2017). New real-time methods for operator situational awareness retrieval and higher process safety in the control room. 3rd Annual IEEE International Symposium on Systems Engineering, ISSE 2017, Vienna, Austria, October 11-13, 2017. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/SysEng.2017.8088300
Wiles, Janet, Worthy, Peter, Hensby, Kristyn, Boden, Marie, Heath, Scott, Pounds, Paul, Rybak, Nikodem, Smith, Michael, Taufotofua, Jonathon and Weigel, Jason (2016). Social cardboard: pretotyping a social ethnodroid in the wild. 11th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2016, Christchurch, New Zealand, 7-10 March 2016. Piscataway, NJ, United States: IEEE. doi: 10.1109/HRI.2016.7451841
Hensby, Kristyn, Wiles, Janet, Boden, Marie, Heath, Scott, Nielsen, Mark, Pounds, Paul, Riddell, Joshua, Rogers, Kristopher, Rybak, Nikodem, Slaughter, Virginia, Smith, Michael, Taufatofua, Jonathon, Worthy, Peter and Weigel, Jason (2016). Hand in hand: tools and techniques for understanding children's touch with a social robot. 11th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2016, Christchurch, New Zealand, 7-10 March 2016. Piscataway, NJ, United States: IEEE Computer Society. doi: 10.1109/HRI.2016.7451794
Research Report
Micklethwaite, Steven, Cook, Nicholas and Rybak, Nikodem (2023). Bowdens Silver - Research Review and Recommendations. Brisbane, Queensland: The University of Queensland, Sustainable Minerals Institute.
Thesis
Rybak, Nikodem (2020). Technical considerations for the application of deep learning methods for multimodal emotion recognition. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland. doi: 10.14264/bf3427d