Dr Nikodem Rybak

Research Fellow – Machine Learning and Natural Language Processing

MISHC

n.rybak@uq.edu.au

Dr Nikodem Rybak, is a machine learning, natural language processing and complex systems research engineer at The University of Queensland.

Nikodem's main area of research is artificial intelligence-driven problem solving for complex systems including language, human economies and political systems, climate, nervous systems, cells and organisms, as well as modern information, energy and telecommunication infrastructures.

Nikodem holds a PhD in Computer Science from The University of Queensland, which focused on the application of machine learning, data reconstruction and signal processing for behavioral modelling. He has over 10 years’ experience working in industry and in academia developing and leading innovative projects in the areas of artificial intelligence, complex systems, machine learning and signal processing.

Collaborations

Nikodem is currently collaborating on artificial intelligence solutions for risk management, predictive analytics as well as natural language processing and advance data visualisation methods for Resourcing Decarbonisation Strategic Funding.

Nik is the program leader for the Artifical Intelligence Health Safety and Environmental Risk Management program.

Funding

Resourcing Decarbonisation Strategic Funding -- 818RD003

Publications

Book Chapters (3)

Journal Articles (3)

Conference Papers (4)

Research Report (1)

Thesis (1)

Book Chapters

Rybak, Nikodem and Hassall, Maureen (2024). Artificial Intelligence Applications for Workplace Safety : An In-Depth Examination. Advances in Information Quality and Management. (pp. 1-19) 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. 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