1336473
Dr Tharindu Fernando Warnakulasuriya
Faculty of Engineering,
School of Electrical Engineering & Robotics
Biography
Dr. Tharindu (Fernando) Warnakulasuriya is a Research Fellow in the Signal Processing, Artificial Intelligence, and Vision Technologies (SAIVT) research program in the School of Electrical Engineering and Robotics (EER) at Queensland University of Technology (QUT). He received his BSc (special degree in computer science) from the University of Peradeniya, Sri Lanka, and his PhD from QUT, Australia. He was awarded a QUT Outstanding Doctoral Thesis Award in recognition of ground-breaking innovative research. Since the completion of his PhD, Tharindu has been conducting interdisciplinary research activities and collaborating with researchers in healthcare, neuroscience, psychology, and computer vision to solve challenging problems in several domains, utilising the advances that he contributed to the area of Machine Learning during his PhD and beyond. He received the QUT Early Career Researcher Award in 2022 and the EER Rising Start Award in 2023.Research highlights:
- Neural memory plasticity for medical anomaly detection.
- Automated system for Terminal Area Air Traffic Prediction.
- Algorithm to Predict Tennis Players' Next Shots.
- Computer-Aided System for Abnormal Event Detection from Surveillance Feeds.
- Autonomous Steering and Driver Behaviour Prediction for Autonomous Cars.
- Monitoring Intuitive Expertise of Airport Security Screeners.
Personal details
Positions
- Research Fellow
Faculty of Engineering,
School of Electrical Engineering & Robotics
Keywords
Artificial intelligence, Deep Learning, Neural Memory Networks, Computer Vision, Abnormal Event Detection, Visual Salience Prediction, Biomedical Signal Processing, Pattern Recognition, Intelligent Surveillance, Image Processing
Research field
Artificial intelligence, Machine learning, Electrical engineering
Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2020
Qualifications
- Doctor of Philosophy (Queensland University of Technology)
Professional memberships and associations
Teaching
Teaching Overview:
- Unit Coordinator EGH404, 2024 Semster 2
- Lecturer EGB103, 2024
- Assessor, EGH400-1/EGH400-2, 2023, 2024
- Assessor, EGH444, 2022, 2023
- Guest Lecturer, EGH444, 2022, 2023
- Guest Lecturer, EGB101, 2023
Experience
Research Areas
- Machine Learning: Deep Learning, Recurrent Neural Networks, Neural Memory Networks, Interpretable Machine Learning, Generative Adversarial Networks, Generative Adversarial Imitation Learning, Deep Inverse Reinforcement Learning, Multimodal Deep Learning.
- Biomedical Signal Processing: Abnormality Detection, Medical Imaging, Biosignal Classification.
- Computer Vision: Human Behaviour Analysis and Prediction, Person Tracking, Saliency Prediction, Image Forensics.
- Sports Analytics: Player Behaviour Analysis and Prediction.
Research Applications:
- Machine Learning: Neural Memory Plasticity, Deep Context Modelling, Structured Memory Networks, Attention Driven Fusion, Recurrent Attention Networks.
- Biomedical Signal Processing: Heart State Segmentation, Abnormal Heart Sound Detection, Automated Schizophrenia Risk Detection.
- Computer Vision: Pedestrian Trajectory Prediction, Aircraft Trajectory Prediction, Monitoring Intuitive Expertise of Airport Security Screeners, Pedestrian Group Detection, Autonomous Steering, Discovering Hidden Temporal Patterns, Human Action Recognition.
- Sports Analytics: Next Shot Prediction in Tennis, Player Strategy Analysis, Soccer Event Analysis.
Professional Service
- Reviewer: IEEE Transactions on Information Forensics and Security; IEEE Transactions on Neural Networks and Learning Systems; Journal of Biomedical and Health Informatics; IEEE Transactions on Circuits and Systems for Video Technology.
Publications
Research outputs by year
- Fernando, T., Gammulle, H., Sridharan, S., Denman, S. & Fookes, C. (2025). Remembering What Is Important: A Factorised Multi-Head Retrieval and Auxiliary Memory Stabilisation Scheme for Human Motion Prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 47(3), 1941–1957. https://eprints.qut.edu.au/254548
- Fernando, T., Priyasad, D., Sridharan, S. & Fookes, C. (2024). Decoupled and Explainable Associative Memory for Effective Knowledge Propagation. IEEE Transactions on Neural Networks and Learning Systems. https://eprints.qut.edu.au/253873
- Fernando, T., Fookes, C., Gammulle, H., Denman, S. & Sridharan, S. (2023). Toward On-Board Panoptic Segmentation of Multispectral Satellite Images. IEEE Transactions on Geoscience and Remote Sensing, 61. https://eprints.qut.edu.au/239473
- Fernando, T., Gammulle, H., Denman, S., Sridharan, S. & Fookes, C. (2022). Deep Learning for Medical Anomaly Detection: A Survey. ACM Computing Surveys, 54(7). https://eprints.qut.edu.au/214059
- Fernando, T., Sridharan, S., Denman, S. & Fookes, C. (2022). Split 'n' merge net: A dynamic masking network for multi-task attention. Pattern Recognition, 126. https://eprints.qut.edu.au/232375
- Fernando, T., Denman, S., Sridharan, S. & Fookes, C. (2021). Deep Inverse Reinforcement Learning for Behavior Prediction in Autonomous Driving: Accurate Forecasts of Vehicle Motion. IEEE Signal Processing Magazine, 38(1), 87–96. https://eprints.qut.edu.au/210194
- Fernando, T., Fookes, C., Denman, S. & Sridharan, S. (2021). Detection of Fake and Fraudulent Faces via Neural Memory Networks. IEEE Transactions on Information Forensics and Security, 16, 1973–1988. https://eprints.qut.edu.au/210209
- Sridharan, S., Fookes, C., Gammulle, P., Warnakulasuriya, T. & Denman, S. (2019). Coupled generative adversarial network for continuous fine-grained action segmentation. Proceedings of the 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 200–209. https://eprints.qut.edu.au/126905
- Warnakulasuriya, T., Denman, S., Sridharan, S. & Fookes, C. (2019). GD-GAN: Generative adversarial networks for trajectory prediction and group detection in crowds. Computer Vision - ACCV 2018: 14th Asian Conference on Computer Vision, Revised Selected Papers, Part I (Lecture Notes in Computer Science, Volume 11361), 314–330. https://eprints.qut.edu.au/126868
- Warnakulasuriya, T., Denman, S., Sridharan, S. & Fookes, C. (2018). Soft + Hardwired attention: An LSTM framework for human trajectory prediction and abnormal event detection. Neural Networks, 108, 466–478. https://eprints.qut.edu.au/126862
QUT ePrints
For more publications by Tharindu Fernando, explore their research in QUT ePrints (our digital repository).
Awards
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2024
- Details
- QUT Faculty of Engineering Early Career Achievement Award
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2023
- Details
- QUT School of Electrical Engineering and Robotics Rising Start Award
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2019
- Details
- 2019 QUT University Award for Outstanding Doctoral Thesis
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2015
- Details
- University Award for Academic Excellence, University of Peradeniya, Sri Lanka
Supervision
Looking for a postgraduate research supervisor?
I am currently accepting research students for Honours, Masters and PhD study.
You can browse existing student topics offered by QUT or propose your own topic.
Current supervisions
- Lifelong Collaborative Learning
PhD, Associate Supervisor
Other supervisors: Emeritus Professor Sridha Sridharan, Adjunct Professor Peyman Moghadam, Professor Clinton Fookes - Deep Multimodal Learning for Trajectory Prediction in Real-world Applications
PhD, Principal Supervisor
Other supervisors: Professor Clinton Fookes, Emeritus Professor Sridha Sridharan - Self-Supervised Learning for 3D Multimodal Perception
PhD, Associate Supervisor
Other supervisors: Professor Clinton Fookes, Adjunct Professor Peyman Moghadam, Emeritus Professor Sridha Sridharan - Deep Spatial-Spectral Representation Learning for Hyperspectral Data
PhD, Associate Supervisor
Other supervisors: Emeritus Professor Sridha Sridharan, Adjunct Professor Peyman Moghadam, Professor Clinton Fookes, Dr Maryam Haghighat - Robust Multi-modal Machine Learning Model for Handling Corrupted and Missing Inputs
PhD, Associate Supervisor
Other supervisors: Associate Professor Simon Denman, Professor Clinton Fookes - Deep Learning for Air quality from Space
PhD, Associate Supervisor
Other supervisors: Professor Clinton Fookes, Distinguished Professor Lidia Morawska, Dr Kien Nguyen Thanh - Human Action Recognition for Real World Applications
PhD, Associate Supervisor
Other supervisors: Emeritus Professor Sridha Sridharan, Professor Clinton Fookes, Dr Harshala Gammulle - Discovering novel strategies with Reinforcement Learning
PhD, Associate Supervisor
Other supervisors: Associate Professor Simon Denman, Dr Kien Nguyen Thanh
Completed supervisions (Doctorate)
The supervisions listed above are only a selection.