
PhD (University of Queensland)
Professor Milford conducts interdisciplinary research at the boundary between robotics, neuroscience and computer vision and is a multi-award winning educational entrepreneur. His research models the neural mechanisms in the brain underlying tasks like navigation and perception to develop new technologies in challenging application domains such as all-weather, anytime positioning for autonomous vehicles. He is also one of Australia’s most in demand experts in technologies including self-driving cars, robotics and artificial intelligence, and is a passionate science communicator. He currently holds the position of Professor at the Queensland University of Technology, as well as Australian Research Council Future Fellow, Microsoft Research Faculty Fellow and Chief Investigator at the Australian Centre for Robotic Vision.
His research has helped attract more than 45 million dollars in research and industry funding for fellowships and team grants from organizations including the Australian Research Council, Microsoft and US Air Force. Michael’s papers have won (6) or been finalists (9) for 15 best paper awards including the 2012 ICRA Best Vision paper. His citation h-index is 33, with 5884 citations as of March 2020. Michael has dual Australian-US citizenship and has lived and worked in locations including Boston, Edinburgh and London. He has collaborated with organizations including Harvard University, Boston University, Oxford University, MIT, Edinburgh University, Imperial College London, Google Deepmind, Caterpillar, the US Air Force and NASA’s Jet Propulsion Laboratory.
Michael has given more than 200 keynotes, plenaries and invited presentations at major industrial corporations (Google, Amazon, Microsoft, Toyota, OpenAI, Uber), top universities (including Harvard University, MIT, Oxford University, CMU, Imperial College London, Cambridge and Boston University), international conferences, workshops and scientific meetings across thirteen countries (USA, Canada, UK, Japan, China, Portugal, Norway, Germany, Italy, Singapore, Austria, France and Australia) to audiences of up to 2000 people. His work has been recognized by many international and national awards including the 2019 Batterham Medal for Engineering Excellence, the 2015 Queensland Young Tall Poppy Scientist of the Year award and a Microsoft Research Faculty Fellowship.
As a lifelong educational entrepreneur, Michael has written innovative textbooks, novels and storybooks (20 titles to date) for early childhood, primary and high school audiences, and collaborates with the major movie studio representatives to write a regular “science in the movies” review series. He recently launched the company Math Thrills which combines mass market entertainment and STEM education. Math Thrills has received funding from Kickstarter, QUTBluebox and the AMP Foundation and honours including the Queensland Young Tall Poppy of the Year Award, being a Reimagine Education Awards finalist, a TedXQUT talk and World Science Festival event. His company has sold in 35 countries to date with recent titles including the STEM Storybook, The Complete Guide to Artificial Intelligence for Kids, Robot Revolution and Rachel Rocketeer.
Projects
- [COMPLETED] ARC Future Fellowship: Superhuman place recognition
- [COMPLETED] Automation-enabling positioning for underground mining
- [COMPLETED] How automated vehicles will interact with road infrastructure
- AUSMURI: Neuro-Autonomy: Neuroscience-Inspired Perception, Navigation, and Spatial Awareness for Autonomous Robots
- Australian Research Council Industrial Transformation Training Centre for Joint Biomechanics
- Automated Early-Detection of the Invasive Grass African Lovegrass
- Contextual Hazard Detection
- Evaluating the effect of illumination on the performance of visual odometry in underground mining environments
- HD maps for automated driving
- Mini Autonomous Vehicles
- Reinforcement Learning for Robot Navigation
- Reliability in Deep Machine Learning and Uncertainty for Object Detection
- Rheinmetall Defence Australia: Advanced Terrain Detection (ATD)
- Scene Understanding and Semantic SLAM
- US Air Force / AOARD: An infinitely scalable learning and recognition network
- Visual Place Recognition for Robotics in Extreme Environments
Additional information
Professor Milford conducts interdisciplinary research at the boundary between robotics, neuroscience and computer vision and is a multi-award winning educational entrepreneur. His research models the neural mechanisms in the brain underlying tasks like navigation and perception to develop new technologies in challenging application domains such as all-weather, anytime positioning for autonomous vehicles. He is also one of Australia’s most in demand experts in technologies including self-driving cars, robotics and artificial intelligence, and is a passionate science communicator. He currently holds the position of Professor at the Queensland University of Technology, as well as Australian Research Council Future Fellow, Microsoft Research Faculty Fellow and Chief Investigator at the Australian Centre for Robotic Vision.
His research has helped attract more than 45 million dollars in research and industry funding for fellowships and team grants from organizations including the Australian Research Council, Microsoft and US Air Force. Michael’s papers have won (6) or been finalists (9) for 15 best paper awards including the 2012 ICRA Best Vision paper. His citation h-index is 33, with 5884 citations as of March 2020. Michael has dual Australian-US citizenship and has lived and worked in locations including Boston, Edinburgh and London. He has collaborated with organizations including Harvard University, Boston University, Oxford University, MIT, Edinburgh University, Imperial College London, Google Deepmind, Caterpillar, the US Air Force and NASA’s Jet Propulsion Laboratory.
Michael has given more than 200 keynotes, plenaries and invited presentations at major industrial corporations (Google, Amazon, Microsoft, Toyota, OpenAI, Uber), top universities (including Harvard University, MIT, Oxford University, CMU, Imperial College London, Cambridge and Boston University), international conferences, workshops and scientific meetings across thirteen countries (USA, Canada, UK, Japan, China, Portugal, Norway, Germany, Italy, Singapore, Austria, France and Australia) to audiences of up to 2000 people. His work has been recognized by many international and national awards including the 2019 Batterham Medal for Engineering Excellence, the 2015 Queensland Young Tall Poppy Scientist of the Year award and a Microsoft Research Faculty Fellowship.
As a lifelong educational entrepreneur, Michael has written innovative textbooks, novels and storybooks (20 titles to date) for early childhood, primary and high school audiences, and collaborates with the major movie studio representatives to write a regular “science in the movies” review series. He recently launched the company Math Thrills which combines mass market entertainment and STEM education. Math Thrills has received funding from Kickstarter, QUTBluebox and the AMP Foundation and honours including the Queensland Young Tall Poppy of the Year Award, being a Reimagine Education Awards finalist, a TedXQUT talk and World Science Festival event. His company has sold in 35 countries to date with recent titles including the STEM Storybook, The Complete Guide to Artificial Intelligence for Kids, Robot Revolution and Rachel Rocketeer.
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2019
- Details
- 2019 Batterham Medal for Engineering Excellence awarded by the Australian Academy of Technology and Engineering
- Type
- Fellowships
- Reference year
- 2013
- Details
- Microsoft Research Faculty Fellowship, $110,000
- Type
- Membership of Review Panels on Prestigious Grant Applications
- Reference year
- 2016
- Details
- Australian Research Council for Discovery Projects and Discovery Early Career Outstanding Researcher Fellowships
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2013
- Details
- Best Paper Finalist "Towards Condition-Invariant, Top-Down Visual Place Recognition," Michael Milford, Walter Scheirer, Eleonora Vig and David Cox
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2013
- Details
- Ray Jarvis Best Paper Award "Towards Bio-inspired Place Recognition over Multiple Spatial Scales," Zetao Chen, Adam Jacobson, Ugur Murat Erdem, Michael Hasselmo and Michael Milford
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2016
- Details
- Best Paper Finalist Robotics Science and Systems Conference: Milford, M., "Visual Route Recognition with a Handful of Bits", Sydney, Australia, 2012.
- Type
- Membership of Review Panels on Prestigious Grant Applications
- Reference year
- 2013
- Details
- Israeli Ministry of Science & Technology reviewer for Brain Research Infrastructure program grant reviewer
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2012
- Details
- Best Robot Vision Paper Award at the 2012 International Conference on Robotics and Automation
- Type
- Membership of Review Panels on Prestigious Grant Applications
- Reference year
- 2012
- Details
- Canadian Natural Sciences and Engineering Research Council Reviewer for Discovery Grants
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2006
- Details
- Queensland Young Achiever of the Year (Science and Technology) The aims are objectives of the program are to: Acknowledge & highlight the achievements of young Australians. Educate the general public with examples of youth achievement. Encourage & motivate young Australians at all levels in their chosen field of endeavour. Develop a sense of pride in being an Australian. Build self-confidence through rewards for excellence. Provide role models & mentors for our youth by highlighting their achievements and the pursuit of excellence. Develop and encourage leadership and life skills in young Australians.
- Milford M, (2013) Vision-based place recognition: how low can you go?, International Journal of Robotics Research p766-789
- Ball D, Heath S, Wiles J, Wyeth G, Corke P, Milford M, (2013) OpenRatSLAM: an open source brain-based SLAM system, Autonomous Robots p149-176
- Maddern W, Milford M, Wyeth G, (2012) CAT-SLAM: probabilistic localisation and mapping using a continuous appearance-based trajectory, International Journal of Robotics Research p429-451
- Maddern W, Milford M, Wyeth G, (2012) Capping computation time and storage requirements for appearance-based localization with CAT-SLAM, Proceedings of the 2012 IEEE International Conference on Robotics and Automation p822-827
- Milford M, Wyeth G, (2012) SeqSLAM: Visual route-based navigation for sunny summer days and stormy winter nights, Proceedings of the 2012 IEEE International Conference on Robotics and Automation p1643-1649
- Milford M, (2012) Visual route recognition with a handful of bits, Robotics: Science and Systems VIII - Proceedings of the 8th Robotics: Science and Systems Conference p297-304
- Milford M, Wiles J, Wyeth G, (2010) Solving navigational uncertainty using grid cells on robots, PLoS Computational Biology p1-14
- Milford M, Wyeth G, (2010) Persistent navigation and mapping using a biologically inspired SLAM system, International Journal of Robotics Research p1131-1153
- Milford M, (2008) Robot navigation from nature: Simultaneous localisation, mapping, and path planning based on hippocampal models
- Milford M, Wyeth G, (2008) Mapping a suburb with a single camera using a biologically inspired SLAM system, IEEE Transactions on Robotics p1038-1053
- Title
- ARC Centre of Excellence for Robotic Vision (ACRV)
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- CE140100016
- Start year
- 2014
- Keywords
- Robotic Vision; Robotics; Computer Vision
- Title
- Superhuman Place Recognition with a Unified Model of Human Visual Processing and Rodent Spatial Memory
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- FT140101229
- Start year
- 2015
- Keywords
- Place Recognition; Spatial Memory; Bio-Inspired Robot Navigation
- Title
- Visual Navigation for Sunny Summer Days and Stormy Winter Nights
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DE120100995
- Start year
- 2012
- Keywords
- Vision-Based Navigation; Robot Navigation; Change-Invariant
- Title
- ARC Industrial Transformation Training Centre for Joint Biomechanics
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- IC190100020
- Start year
- 2020
- Keywords
- Insect brain-inspired learning algorithms for visual place recognition
PhD, Principal Supervisor
Other supervisors: Distinguished Professor Peter Corke - Condition-Invariant Surface-Based Visual Localisation for Multiple Domains and Environments
PhD, Principal Supervisor
Other supervisors: Professor Les Dawes - Recognition Inspired by Human Visual Processing
PhD, Principal Supervisor
Other supervisors: Dr Adam Jacobson - Global relocalization across changing conditions for metric, keyframe-based visual SLAM systems
PhD, Principal Supervisor
Other supervisors: Associate Professor Niko Suenderhauf - Uncertainty from Convolutional Neural Networks for Robotic Vision
PhD, Mentoring Supervisor
Other supervisors: Dr Feras Dayoub - Utilizing Semantic Information to Improve Reinforcement Learning Outcomes
PhD, Mentoring Supervisor
Other supervisors: Associate Professor Niko Suenderhauf - Surface Crack Detection and Localisation with Active Perception for Automated Underground Mine Void Characterisation
PhD, Associate Supervisor
Other supervisors: Associate Professor Thierry Peynot, Associate Professor Felipe Gonzalez - High-fidelity Simulation for Robot Vision
PhD, Associate Supervisor
Other supervisors: Distinguished Professor Peter Corke - UAV Navigation using Semantic Cues
PhD, Associate Supervisor
Other supervisors: Associate Professor Felipe Gonzalez
- Direct Visual Hazard Affordance Detection (2019)
- Human Action Recognition and Prediction for Robotics Applications (2019)
- Robust Visual Place Recognition under Simultaneous Variations in Viewpoint and Appearance (2019)
- Bio-Inspired Multi-Sensor Fusion and Calibration for Robot Place Learning and Recognition (2018)
- Learning Real-World Visuo-Motor Policies from Simulation (2018)
- Biologically-inspired Place Recognition with Neural Networks (2016)
- Visual Sequence-Based Place Recognition for Changing Conditions and Varied Viewpoints (2016)
- Continuous Appearance-Based Localisation and Mapping (2014)
- Visual Place Recognition for Persistent Robot Navigation in Changing Environments (2014)