Ruwan Tennakoon

Dr. Ruwan Tennakoon

Senior Lecturer

Details

  • College: School of Computing Technologies
  • Department: School of Computing Technologies
  • Campus: City Campus Australia
  • ruwan.tennakoon@rmit.edu.au

Open to

  • Masters Research or PhD student supervision

About

Dr Ruwan Tennakoon is a Senior Lecturer in Artificial Intelligence at the School of Computing Technologies, RMIT University, Melbourne, Australia. He earned his BSc (Hons) in Electrical and Electronics Engineering from the University of Peradeniya and completed his PhD in Computer Vision at Swinburne University of Technology in 2015. Following his PhD, he undertook post-doctoral fellowships at the RMIT School of Engineering and IBM Research.

Ruwan’s research focuses on robust computer vision, with applications in medical imaging and industrial automation. His early work focused on developing robust algorithms for low-level vision tasks. More recently, he has been addressing the challenges of distribution shift in vision systems, with a particular interest in understanding large vision foundation models.

Research fields

  • 460304 Computer vision
  • 460308 Pattern recognition
  • 400304 Biomedical imaging
  • 4611 Machine learning

Academic positions

  • Senior Lecturer-Artificial Intelligence
  • RMIT University
  • School of Computing Technologies
  • Melbourne, Australia
  • Jan 2022 – Present
  • Lecturer
  • RMIT University
  • School of Computing Technologies
  • Melbourne, Australia
  • May 2019 – Dec 2021
  • Research Fellow
  • RMIT University
  • School of Engineering
  • Melbourne, Australia
  • Apr 2017 – May 2019
  • Post-Doctoral Researcher
  • IBM Research – Australia
  • Melbourne, Australia
  • May 2016 – Apr 2017
  • Post-Doctoral Researcher
  • RMIT University
  • School of Engineering
  • Melbourne, Australia
  • Feb 2015 – May 2016

Supervisor projects

  • Robust Computer vision for surveillance and threat detection
  • 2 Oct 2024
  • Predicting brain disorders with graph learning
  • 22 Aug 2024
  • Computational Modeling for Visual Attention using Eye Gaze Tracking in Dynamic Scene
  • 6 Mar 2024
  • Learning Robust and Generalisable Models for Computer Vision Using Animation
  • 21 Dec 2023
  • High Rate Manufacturing Technologies For Preforming Complex Composite Aerostructures
  • 12 Dec 2023
  • Digital Manufacturing Technologies
  • 5 Dec 2023
  • A Deep Learning Based Framework for Prostate Cancer Detection in Computer Tomography
  • 28 Nov 2023
  • Detecting prostate cancer for radiotherapy treatments using deep learning approaches
  • 27 Oct 2023
  • Learning Robust and Generalisable Models for Computer Vision Using Animation
  • 17 Oct 2023
  • Robust Stereo Vision System
  • 26 Apr 2023
  • Computer Vision based Automated Visual Inspection of Transparent Packaging
  • 14 Apr 2023
  • Data-efficient Machine Learning for Robotic Perception and Manipulation
  • 13 Mar 2023
  • Learning Robust and Generalisable Models for Computer Vision Using Animation
  • 9 Mar 2023
  • Application of AI techniques to Positron Emission Tomography (PET) imaging
  • 13 Dec 2021
  • Off-line Handwritten Text Recognition with Cross-outs and Corrections Using Deep Learning
  • 20 Oct 2020
  • Learning Robust Models for Medical Imaging Applications
  • 20 Dec 2019
  • Identification of Moving Objects in Complex Dynamic Scenes Using Semantics
  • 24 Oct 2019
  • Passive Visual Depth Estimation in the Deep Learning Era
  • 26 Jul 2019
  • Robust 3D Shape Classification: A Machine Learning Approach
  • 28 Nov 2018
  • Machine Learning for Volumetric Data Analysis of Bread Dough: Meeting the Synchrotron Challenge
  • 2 Jul 2018
  • Improved Image Analysis by Maximised Statistical Use of Geometry-Shape Constraints
  • 14 Aug 2017

Teaching interests

Computer vision, Machine learning

Research interests

Artificial Intelligence, Computer vision and Image Processing, Medical Imaging, Manufacturing Engineering, Industry Automation

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Acknowledgement of Country

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Sentient' by Hollie Johnson, Gunaikurnai and Monero Ngarigo.