Research Interests:
● Deep Learning
● Bayesian Modelling
● Physics Informed Machine Learning
● Time Series Analysis
●
Current Institution:
Data61, CSIRO (The Commonwealth Scientific and Industrial Research Organisation), Australia.
Academic Qualifications:
- PhD (University of Pretoria)
- Honours in Electronic Engineering (University of Pretoria)
- Bachelor of Electrical and Electronic Engineering (University of Johannesburg)
Links:
Google Scholar:
G6icCU4AAAAJ
GitHub:
https://github.com/jjdabr
LinkedIn:
https://au.linkedin.com/in/joel-dabrowski-a7a99716b
CSIRO:
https://people.csiro.au/d/j/joel-dabrowski
Papers (first author pre-prints)
2023
- Fruit Picker Activity Recognition with Wearable Sensors and Machine Learning, JJ Dabrowski, A Rahman, IEEE International Joint Conference on Neural Networks (IJCNN), 2023
- Bayesian Physics Informed Neural Networks for data assimilation and spatio-temporal modelling of wildfires, JJ Dabrowski, DE Pagendam, J Hilton, C Sanderson, D MacKinlay, C Huston, A Bolt, P Kuhnert, Spatial Statistics, 2023
- Quality Control in Weather Monitoring with Dynamic Linear Models, JJ Dabrowski, A Rahman, M Li, Q Shao, S Bakar, A Powell, B Henderson, The 2nd AAAI Workshop on AI for Agriculture and Food Systems, 2023
2022
- Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution, JJ Dabrowski, DE Pagendam, arXiv Preprint, 2022
- Towards Data Assimilation in Level-Set Wildfire Models Using Bayesian Filtering, JJ Dabrowski, C Huston, J Hilton, S Mangeon, P Kuhnert, arXiv Preprint, 2022
- Deep Learning for Prawn Farming: Forecasting and Anomaly Detection, JJ Dabrowski, A Rahman, A Hellicar, M Rana, S Arnold, Advances in Knowledge Discovery and Data Mining. PAKDD 2022. Lecture Notes in Computer Science, vol 13282
2020
2019
- Deep Learning and Statistical Models for Time-Critical Pedestrian Behaviour Prediction, JJ Dabrowski, JP de Villiers, A Rahman, C Beyers, International Conference on Neural Information Processing, 458-465, 2019
- Sequence-to-Sequence Imputation of Missing Sensor Data, JJ Dabrowski, A Rahman, Australasian Joint Conference on Artificial Intelligence, 265-276, 2019
2018
- Prediction of dissolved oxygen from pH and water temperature in aquaculture prawn ponds, JJ Dabrowski, A Rahman, A George, Proceedings of the Australasian joint conference on artificial intelligence …, 3, 2018
- State space models for forecasting water quality variables: an application in aquaculture prawn farming, JJ Dabrowski, A Rahman, A George, S Arnold, J McCulloch, Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 10, 2018
- Naïve Bayes switching linear dynamical system: A model for dynamic system modelling, classification, and information fusion, JJ Dabrowski, JP de Villiers, C Beyers, Information Fusion 42, 75-101, 5, 2018
2017
2016
2015
- A unified model for context-based behavioural modelling and classification, JJ Dabrowski, JP De Villiers, Expert Systems with Applications 42 (19), 6738-6757, 11, 2015
- Maritime piracy situation modelling with dynamic Bayesian networks, JJ Dabrowski, JP De Villiers, Information fusion 23, 116-130, 35, 2015
- Contextual behavioural modelling and classification of vessels in a maritime piracy situation, JJ Dabrowski, University of Pretoria, 2015,