Overview
Background
Dr Alina Bialkowski is a computer vision & machine learning researcher developing interpretable machine learning models to increase the performance and transparency of Artificial Intelligence (AI) decision-making. Her research interests include quantifying and extracting actionable knowledge from data to solve real-world problems and giving human understanding to AI models through feature visualisation and attribution methods. She has applied these techniques to various multi-disciplinary applications such as medical imaging (including imaging strokes in the brain using the new sensing modality of electromagnetic imaging), modelling human attention in driving, intelligent transport systems (ITS), intelligent surveillance, and sports analytics.
Dr Bialkowski holds a PhD and BEng (Electrical Engineering) from the Queensland University of Technology, Australia. Her doctoral studies were in characterising group behaviours from visual and spatio-temporal data to enhance statistics and visualisation in sports analytics as well as intelligent surveillance systems. She spent a year at Disney Research Pittsburgh where she developed techniques to automatically analyse team sports, followed by 2.5 years as a postdoctoral researcher at the University College London, developing deep neural networks to better understand human perception and attention in driving, before joining UQ in late 2017.
The impact of her research is evidenced by the high number of citations to her work (>1600 citations and an h-index of 20 according to Google Scholar) and awards including a best paper prize in 2017 at WACV (a top computer vision conference). In addition to high impact journals and conferences, her work has resulted in 6 international patents filed with Disney Research, Toyota Motor Europe, University College London, and The University of Queensland.
Availability
- Dr Alina Bialkowski is:
- Available for supervision
- Media expert
Fields of research
Qualifications
- Bachelor (Honours), Queensland University of Technology
- Doctor of Philosophy, Queensland University of Technology
Research interests
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Machine Learning
Developing interpretable or explainable models to increase trust and transparency of computer-based decisions.
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Computer Vision
Developing models of visual information using image processing and feature representation learning approaches such as deep learning to perform predictions on data.
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Sensors
Utilising sensors such as cameras and antennas/electromagnetic sensors to enable remote sensing and non-invasive imaging.
Works
Search Professor Alina Bialkowski’s works on UQ eSpace
2014
Book Chapter
Representing team behaviours from noisy data using player role
Bialkowski, Alina, Lucey, Patrick, Carr, Peter, Sridharan, Sridha and Matthews, Iain (2014). Representing team behaviours from noisy data using player role. Computer Vision in Sports. (pp. 247-269) Cham, Switzerland: Springer . doi: 10.1007/978-3-319-09396-3_12
2013
Conference Publication
Person re-identification using group information
Bialkowski, Alina, Lucey, Patrick, Wei, Xinyu and Sridharan, Sridha (2013). Person re-identification using group information. 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Hobart, Tasmania, 26-28 November 2013. Red Hook, NY, United States: Curran Associates. doi: 10.1109/dicta.2013.6691512
2013
Conference Publication
Representing and Discovering Adversarial Team Behaviors Using Player Roles
Lucey, Patrick, Bialkowski, Alina, Carr, Peter, Morgan, Stuart, Matthews, Iain and Sheikh, Yaser (2013). Representing and Discovering Adversarial Team Behaviors Using Player Roles. 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Portland, Oregon, 23-28 June 2013. Red Hook, NY, United States: Curran Associates. doi: 10.1109/cvpr.2013.349
2013
Conference Publication
Recognising team activities from noisy data
Bialkowski, Alina, Lucey, Patrick, Carr, Peter, Denman, Simon, Matthews, Iain and Sridharan, Sridha (2013). Recognising team activities from noisy data. 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Portland, OR, United States, 23-28 June 2013. New York, NY, United States: IEEE. doi: 10.1109/cvprw.2013.143
2012
Conference Publication
Characterizing multi-agent team behavior from partial team tracings: Evidence from the english premier league
Lucey, Patrick, Bialkowski, Alina, Carr, Peter, Foote, Eric and Matthews, Iain (2012). Characterizing multi-agent team behavior from partial team tracings: Evidence from the english premier league. AAAI Conference on Artificial Intelligence, Toronto, Canada, 22-26 July 2012. Reston, VA United States: AAAI Press. doi: 10.1609/aaai.v26i1.8246
2012
Book Chapter
Identifying Customer Behaviour and Dwell Time Using Soft Biometrics
Denman, Simon, Bialkowski, Alina, Fookes, Clinton and Sridharan, Sridha (2012). Identifying Customer Behaviour and Dwell Time Using Soft Biometrics. Video Analytics for Business Intelligence. (pp. 199-238) Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-28598-1_7
2012
Conference Publication
A database for person re-identification in multi-camera surveillance networks
Bialkowski, Alina, Denman, Simon, Sridharan, Sridha, Fookes, Clinton and Lucey, Patrick (2012). A database for person re-identification in multi-camera surveillance networks. 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA), Fremantle, Western Australia, 3-5 December 2012. Red Hook, NY, United States: Curran Associates. doi: 10.1109/dicta.2012.6411689
2012
Conference Publication
Can you describe him for me? A technique for semantic person search in video
Denman, Simon, Halstead, Michael, Bialkowski, Alina, Fookes, Clinton and Sridharan, Sridha (2012). Can you describe him for me? A technique for semantic person search in video. 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA), Fremantle, Western Australia, 3-5 December 2012. Red Hook, NY, United States: Curran Associates. doi: 10.1109/dicta.2012.6411729
2012
Journal Article
Identifying Customer Behaviour and Dwell Time Using Soft Biometrics
Denman, Simon, Bialkowski, Alina, Fookes, Clinton and Sridharan, Sridha (2012). Identifying Customer Behaviour and Dwell Time Using Soft Biometrics. Video Analytics for Business Intelligence, 409, 199-238.
2011
Conference Publication
Determining operational measures from multi-camera surveillance systems using soft biometrics
Denman, Simon, Bialkowski, Alina, Fookes, Clinton and Sridharan, Sridha (2011). Determining operational measures from multi-camera surveillance systems using soft biometrics. 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Klagenfurt, Austria, 30 August - 2 September 2011. IEEE. doi: 10.1109/avss.2011.6027377
2009
Conference Publication
Soft-biometrics: unconstrained authentication in a surveillance environment
Denman, Simon, Fookes, Clinton, Bialkowski, Alina and Sridharan, Sridha (2009). Soft-biometrics: unconstrained authentication in a surveillance environment. 11th Conference on Digital Image Computing: Techniques and Applications, Melbourne, Australia, 1-3 December 2009. Red Hook, NY, United States: Curran Associates. doi: 10.1109/dicta.2009.38
Supervision
Availability
- Dr Alina Bialkowski is:
- Available for supervision
Before you email them, read our advice on how to contact a supervisor.
Available projects
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AgriTwins Project 5: Implementation of Digital Twin Technology for Environmental Monitoring and Sustainable Land Use Management in Bega Valley
PhD Project 5: Implementation of Digital Twin Technology for Environmental Monitoring and Sustainable Land Use Management in Bega valley
With Bega Group & Regional Circularity Co-operative
Description:
This project aims to apply digital twin technology to map and monitor land use in the production region of Bega Valley focusing on greenhouse gas (GHG) monitoring and enhancing environmental sustainability. This could include, but not exclusively, monitoring of natural capital (carbon and biodiversity), soil moisture, river flows, sequestration, etc.
Utilising data from satellite imagery, drones, sensors, weather stations and any other remote sensing techniques, the digital/quantum twin will integrate all forms of available data with land topography parameters, soil health data, and microclimate data to provide a dynamic and comprehensive representation of the region.
This approach will enable better decision-making and environmental stewardship, enhancing both productivity and sustainability in the Bega Valley.
Objectives:
- Develop a high-resolution digital twin of the region for land use classification.
- Monitor and analyse land topography, resource utilisation, and environmental impacts.
- Optimise land management practices to enhance sustainability and productivity.
- Facilitate with environmental regulations, to support stakeholder collaboration and informed decision-making.
Deliverables:
- Comprehensive digital/quantum twin model of the region, incorporating detailed land use classifications.
- Real-time environmental monitoring dashboard providing up-to-date insights into resource utilisation and environmental impacts.
- Optimisation and decision support tools to aid in sustainable land management practices.
- Reports documenting alignment with environmental and regulatory standards.
- Training and engagement materials to educate stakeholders and promote active participation in sustainable practices.
If interested please email me at alina.bialkowski@uq.edu.au with the subject containing AgriTwins
Supervision history
Current supervision
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Doctor Philosophy
Using deep learning to improve emergency response in natural hazard management
Principal Advisor
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Doctor Philosophy
Robust Deep Learning Models for Microwave Imaging
Principal Advisor
Other advisors: Dr Lei Guo
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Master Philosophy
Experience Saturation: Quantifying Demotivation and Disengagement
Associate Advisor
Other advisors: Professor Julie Henry, Dr Nell Baghaei
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Master Philosophy
Non-Invasive Abundance Monitoring of Captive Mala (Lagorchestes hirsutus) Using Proximal Remote Sensing
Associate Advisor
Other advisors: Associate Professor Diana Fisher, Dr Lorna Hernandez Santin
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Master Philosophy
Explainable decision support for skin cancer detection using machine learning
Associate Advisor
Other advisors: Professor Tim Miller
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Doctor Philosophy
Electromagnetic Solver Using Physics-Guided Deep Neural Network
Associate Advisor
Other advisors: Dr Lei Guo, Professor Amin Abbosh
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Doctor Philosophy
Minimally Invasive Blood Analysis Using Data-Driven Electromagnetic Techniques
Associate Advisor
Other advisors: Associate Professor Konstanty Bialkowski, Dr Lei Guo, Professor Amin Abbosh
Completed supervision
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2024
Doctor Philosophy
Knowledge Distillation for Enhancing Lightweight Computer Vision Models
Principal Advisor
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2025
Doctor Philosophy
Universal Deep Learning for Reliable Electromagnetic Imaging and Detection in Inhomogeneous Media
Associate Advisor
Other advisors: Dr Lei Guo, Professor Amin Abbosh
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2021
Doctor Philosophy
Characterization and Detection of Skin Malignancies Using Microwave Techniques
Associate Advisor
Other advisors: Professor Amin Abbosh
Media
Enquiries
Contact Dr Alina Bialkowski directly for media enquiries about:
- Artificial Intelligence
- Machine Learning
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