Professor Michael Milford
Faculty of Engineering,
School of Electrical Engineering & Robotics
Biography
I conduct interdisciplinary research at the boundary between robotics, neuroscience and computer vision and am a multi-award winning educational entrepreneur. My 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. I am also passionate about engaging and educating all sectors of society around new opportunities and impacts from technology including robotics, autonomous vehicles and artificial intelligence. I currently hold the positions of Australian Research Council Laureate Fellow, Director of the QUT Centre for Robotics, QUT Professor, Microsoft Research Faculty Fellow and am a Fellow of the Australian Academy of Technology and Engineering.I have or am leading or co-leading projects totalling more than 48 million dollars in research and industry funding for fellowships and team grants. My papers have won (6) or been finalists (9) for 15 best paper awards including the 2012 ICRA Best Vision paper. My citation h-index is 50, with 13,182 citations as of November 2023. Awards include a Microsoft Research Faculty Fellowship, the ATSE Batterham Medal and Queensland Young Tall Poppy of the Year. I was named top robotics researcher in Australia by citation impact by The Australian Research Magazine (2023, 21, 19) and was a top 3 finalist for the Australian Museum Eureka Prize for Outstanding Early Career Researcher and the APEC ASPIRE Prize. I have dual Australian-US citizenship and have lived and worked in locations including Boston, Edinburgh and London. I have collaborated with organizations including Harvard University, Boston University, Oxford University, MIT, Google Deepmind, Amazon, Ford, Intel, NVIDIA, Caterpillar, the US Air Force Office of Scientific Research and NASA’s Jet Propulsion Laboratory.
As a lifelong educational entrepreneur, I have created innovative educational resources for students for 20 years, with customers across 35 countries. My company Math Thrills combines mass market entertainment and STEM education to create math-filled young adult fiction and movie-inspired education. Math Thrills has received funding from Kickstarter, QUTBluebox and the AMP Foundation, honours including the Queensland Young Tall Poppy of the Year Award, finalist at the Reimagine Education awards, a TedXQUT talk and a World Science Festival event. We have over 20 titles including The Complete Guides to AI, and Autonomous Vehicles, for Kids, the STEM Storybook and Rachel Rocketeer.
Personal details
Positions
- Professor in Electrical Engineering
Faculty of Engineering,
School of Electrical Engineering & Robotics
Keywords
Robotics, Mapping, Navigation, Localization, Computational Neuroscience, RatSLAM, SeqSLAM, Hippocampus, Entorhinal Cortex
Research field
Artificial intelligence, Neurosciences
Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2020
Qualifications
- PhD (University of Queensland)
Professional memberships and associations
IEEE Senior Member, IEEE Robotics and Automation Society Member, Australian Robotics and Automation Association Member. For more information please see my Google Scholar page: http://scholar.google.com/citations?user=TDSmCKgAAAAJ&hl=en
Teaching
Undergraduate Class Teaching From 2011 - 2015 I taught ENB339 Introduction to Robotics in Semester 2 each year. In it we learnt:
- Robot construction, build a robot using Lego and the NXT controller brick
- Fundamentals of robotics, how to control the end point of a simple robot arm and make it follow a path
- Computer vision, how to interpret images to figure the size, shape and color of objects in the scene
- Connect computer vision to robotics, make your robot move to objects of specific size, shape and color.
Undergraduate Project/Thesis Supervision I supervise a number of undergraduate final year project and Vacation Research Experience (VRES) students each year, who work on research projects ranging from autonomous vehicles to visual place recognition to biologically-inspired neural networks to human-robot interaction. Videos My academic YouTube channel Milfordrobotics has dozens of lectures, tutorials, and practical videos about robotics, with over a million views in total. Teaching-related Grants and Funding Awards
- AMP Tomorrow Fund Winner, $25,000, 2016
- M. Milford, Small Teaching and Learning Grant, 2011-2012, "No Student Left Behind", $5,500
Educational Entrepreneurialism I am now focusing my teaching activities on my educational startup Math Thrills Pty Ltd, with investment and funding support from QUT Bluebox, the AMP Foundation, The Australian Academy of Technology and Engineering and the Australian Institute of Policy & Science: AIPS. Math Thrills hijacks the book, movie and game entertainment students love to consume every day to excite and engage them in mathematical learning. It’s easy and fun to use, linked to curriculum and engages different types of learners through multiple learning modalities including fiction, online animations, blockbuster entertainment and workshops. Developed over 5 years and in school trials since early 2015, Math Thrills has been continually improved and expanded based directly on feedback from hundreds of students and teachers. Winner of multiple state and national awards including being a finalist at the 2018 Reimagine Education awards in San Francisco, the new and much improved Math Thrills program is now available for schools and students.
Experience
I conduct interdisciplinary research at the boundary between robotics, neuroscience and computer vision and am a multi-award winning educational entrepreneur. My 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. I am also passionate about engaging and educating all sectors of society around new opportunities and impacts from technology including robotics, autonomous vehicles and artificial intelligence. I currently hold the positions of Australian Research Council Laureate Fellow, Director of the QUT Centre for Robotics, QUT Professor, Microsoft Research Faculty Fellow and am a Fellow of the Australian Academy of Technology and Engineering.
I have or am leading or co-leading projects totalling more than 48 million dollars in research and industry funding for fellowships and team grants. My papers have won (6) or been finalists (9) for 15 best paper awards including the 2012 ICRA Best Vision paper. My citation h-index is 50, with 13,182 citations as of November 2023. Awards include a Microsoft Research Faculty Fellowship, the ATSE Batterham Medal and Queensland Young Tall Poppy of the Year. I was named top robotics researcher in Australia by citation impact by The Australian Research Magazine (2023, 21, 19) and was a top 3 finalist for the Australian Museum Eureka Prize for Outstanding Early Career Researcher and the APEC ASPIRE Prize. I have dual Australian-US citizenship and have lived and worked in locations including Boston, Edinburgh and London. I have collaborated with organizations including Harvard University, Boston University, Oxford University, MIT, Google Deepmind, Amazon, Ford, Intel, NVIDIA, Caterpillar, the US Air Force Office of Scientific Research and NASA’s Jet Propulsion Laboratory.
As a lifelong educational entrepreneur, I have created innovative educational resources for students for 20 years, with customers across 35 countries. My company Math Thrills combines mass market entertainment and STEM education to create math-filled young adult fiction and movie-inspired education. Math Thrills has received funding from Kickstarter, QUTBluebox and the AMP Foundation, honours including the Queensland Young Tall Poppy of the Year Award, finalist at the Reimagine Education awards, a TedXQUT talk and a World Science Festival event. We have over 20 titles including The Complete Guides to AI, and Autonomous Vehicles, for Kids, the STEM Storybook and Rachel Rocketeer.
Publications
- Milford, M., (2013). Vision-based place recognition: how low can you go? International Journal of Robotics Research, 32(7), 766–789. https://eprints.qut.edu.au/219674
- Ball, D., Heath, S., Wiles, J., Wyeth, G., Corke, P. & Milford, M. (2013). OpenRatSLAM: an open source brain-based SLAM system. Autonomous Robots, 34(3), 149–176. https://eprints.qut.edu.au/219076
- Maddern, W., Milford, M. & Wyeth, G. (2012). CAT-SLAM: probabilistic localisation and mapping using a continuous appearance-based trajectory. International Journal of Robotics Research, 31(4), 429–451. https://eprints.qut.edu.au/49805
- 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, 822–827. https://eprints.qut.edu.au/51540
- 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, 1643–1649. https://eprints.qut.edu.au/51538
- 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, 297–304. https://eprints.qut.edu.au/51415
- Milford, M., Wiles, J. & Wyeth, G. (2010). Solving navigational uncertainty using grid cells on robots. PLoS Computational Biology, 6(11), 1–14. https://eprints.qut.edu.au/39472
- Milford, M. & Wyeth, G. (2010). Persistent navigation and mapping using a biologically inspired SLAM system. International Journal of Robotics Research, 29(9), 1131–1153. https://eprints.qut.edu.au/32815
- Milford, M., (2008). Robot navigation from nature: Simultaneous localisation, mapping, and path planning based on hippocampal models. Springer. https://eprints.qut.edu.au/80428
- Milford, M. & Wyeth, G. (2008). Mapping a suburb with a single camera using a biologically inspired SLAM system. IEEE Transactions on Robotics, 24(5), 1038–1053. https://eprints.qut.edu.au/32812
QUT ePrints
For more publications by Michael, explore their research in QUT ePrints (our digital repository).
Filter publications:
A complete list of publications is available at: https://www.qut.edu.au/about/our-people/academic-profiles/michael.milford
Awards
- Type
- Award or Prize
- Reference year
- 2019
- Details
- 2019 Batterham Medal for Engineering Excellence awarded by the Australian Academy of Technology and Engineering
- Type
- Reviewer, Assessor or Judge
- Reference year
- 2016
- Details
- Australian Research Council for Discovery Projects and Discovery Early Career Outstanding Researcher Fellowships
- Type
- Best Paper/Article/Poster/Presentation
- Reference year
- 2013
- Details
- Australasian Conference on Robotics and Automation| Best Paper Finalist
"Towards Condition-Invariant, Top-Down Visual Place Recognition," Michael Milford, Walter Scheirer, Eleonora Vig and David Cox
- Type
- Best Paper/Article/Poster/Presentation
- Reference year
- 2013
- Details
- Australasian Conference on Robotics and Automation| 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
- Funded Fellowship
- Reference year
- 2013
- Details
- Microsoft Corporation| Microsoft Research Faculty Fellowship, $110,000
- Type
- Reviewer, Assessor or Judge
- Reference year
- 2013
- Details
- Israeli Ministry of Science & Technology| Israeli Ministry of Science & Technology reviewer for Brain Research Infrastructure program grant reviewer
- Type
- Best Paper/Article/Poster/Presentation
- Reference year
- 2012
- Details
- IEEE| Best Robot Vision Paper Award at the 2012 International Conference on Robotics and Automation
- Type
- Nomination/Short Listed for an Award
- Reference year
- 2012
- Details
- Best Paper Finalist Robotics Science and Systems Conference: Milford, M., "Visual Route Recognition with a Handful of Bits", Sydney, Australia, 2012.
- Type
- Reviewer, Assessor or Judge
- Reference year
- 2012
- Details
- Canadian Natural Sciences and Engineering Research Council| Canadian Natural Sciences and Engineering Research Council Reviewer for Discovery Grants
- Type
- Award or Prize
- Reference year
- 2006
- Details
- Awards Australia| 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.
Selected research projects
- 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
- MyMobility Camera Based ROM Validation Project
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- IC190100020
- Start year
- 2021
- Keywords
- Title
- ARC Industrial Transformation Training Centre for Joint Biomechanics
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- IC190100020
- Start year
- 2020
- Keywords
Projects listed above are funded by Australian Competitive Grants. Projects funded from other sources are not listed due to confidentiality agreements.
Supervision
Looking for a postgraduate research supervisor?
I am currently accepting research students for Honours, Masters and PhD study.
- Local positioning system field trials and demos
- Adaptive and efficient robot positioning
- Advancing monitoring of diverse grass pollen with computer vision
- Ubiquitous visual positioning devices
- Terrain traversability
You can browse existing student topics offered by QUT or propose your own topic.
Current supervisions
- Adaptive Deep Learning Architectures for Grass Phenology Detection, Classification, and Future Pollen Release Prediction
PhD, Associate Supervisor
Other supervisors: Professor Janet Davies, Dr Andelija Milic - Analysis and Implementation of Depth-Adaptive Pinhole Models for Underwater Refraction Correction
PhD, Associate Supervisor
Other supervisors: Dr Alejandro Fontan Villacampa, Dr Tobias Fischer - Applying Robotic Vision for Revisiting the Reef
PhD, Associate Supervisor
Other supervisors: Dr Tobias Fischer, Dr Alejandro Fontan Villacampa - Dual Attention Alignment to Improve Safety and Driver Readiness in Automated Driving
PhD, Associate Supervisor
Other supervisors: Professor Sebastien Glaser, Professor Ronald Schroeter, Professor Andry Rakotonirainy - Fast and Robust Event-Driven Visual Place Recognition
PhD, Associate Supervisor
Other supervisors: Dr Tobias Fischer - Introspection for Mobile Robot Localisation in Challenging Environments
PhD, Associate Supervisor
Other supervisors: Associate Professor Thierry Peynot - Learning Local and Global Place Representations for Visual Place Recognition
PhD, Principal Supervisor
Other supervisors: Dr Tobias Fischer - Low-latency visual place recognition with event cameras
PhD, Associate Supervisor
Other supervisors: Dr Tobias Fischer - Multi-Modal Sensor Introspection for Robust Visual Place Recognition
PhD, Principal Supervisor
Other supervisors: Dr Tobias Fischer, Associate Professor Thierry Peynot - Pick Me If You Can: SELECTING RELIABLE OPERATING POINTS FOR VISUAL PLACE RECOGNITION
PhD, Associate Supervisor
Other supervisors: Dr Tobias Fischer
Completed supervisions (Doctorate)
- Heterogeneous Sensing Methodologies for Robust Localisation in Challenging Conditions (2026)
- Mobile Manipulation Control Using Implicit and Explicit Scene Representations (2026)
- Realtime Structured and Visually Correctable Representations for Robotic Manipulation (2026)
- Robust Scene Coordinate Regression for Large-scale Visual Localization (2026)
- Visual Localisation Introspection for Robots and Autonomous Systems (2026)
- Ground-to-Aerial Cross-View Image Matching for Robot Localization (2025)
- Heuristic Based Self-Assessment of Target Localisation During Robot-Assisted Shoulder Surgery (2025)
- Beyond Place Matching for Visual Place Recognition on Robots and Autonomous Vehicles (2024)
- Spiking Neural Networks for Scalable Visual Place Recognition (2024)
- Bridging the divide between Visual Place Recognition and SLAM (2023)
Completed supervisions (Masters by Research)
The supervisions listed above are only a selection.