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 Director of the QUT Centre for Robotics (acting), Professor at the Queensland University of Technology.
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 from funding bodies and industry. 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 39, with 8289 citations as of July 2021. I've won multiple awards including being one of only two Australians to ever win a Microsoft Research Faculty Fellowship, the ATSE Batterham Medal (2019) and the Queensland Young Tall Poppy of the Year (2015). I was named the top robotics researcher in Australia by citation impact by The Australian Research Magazine (2019) and was a top 3 finalist for the Australian Museum Eureka Prize for Outstanding Early Career Researcher (2016), the APEC ASPIRE Prize Finalist (2018) and was a finalist in the Reimagine Education Awards Finalist K12 Category.
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 being a finalist at the Reimagine Education awards, a TedXQUT talk and a World Science Festival event. We have over 20 titles including The Complete Guide to AI 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
Discipline
Artificial Intelligence and Image Processing, Neurosciences
Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2008
Qualifications
- PhD (University of Queensland)
Professional memberships and associations
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 have or am leading or co-leading projects totalling more than 48 million dollars in research and industry funding for fellowships and team grants from funding bodies and industry. 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 39, with 8289 citations as of July 2021. I've won multiple awards including being one of only two Australians to ever win a Microsoft Research Faculty Fellowship, the ATSE Batterham Medal (2019) and the Queensland Young Tall Poppy of the Year (2015). I was named the top robotics researcher in Australia by citation impact by The Australian Research Magazine (2019) and was a top 3 finalist for the Australian Museum Eureka Prize for Outstanding Early Career Researcher (2016), the APEC ASPIRE Prize Finalist (2018) and was a finalist in the Reimagine Education Awards Finalist K12 Category.
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 being a finalist at the Reimagine Education awards, a TedXQUT talk and a World Science Festival event. We have over 20 titles including The Complete Guide to AI 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) p766
- 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) p149
- 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) p429
- 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
- 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
- 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
- Milford M, Wiles J, Wyeth G, (2010) Solving navigational uncertainty using grid cells on robots, PLoS Computational Biology, 6 (11) p1
- Milford M, Wyeth G, (2010) Persistent navigation and mapping using a biologically inspired SLAM system, International Journal of Robotics Research, 29 (9) p1131
- Milford M, (2008) Robot navigation from nature: Simultaneous localisation, mapping, and path planning based on hippocampal models, Springer
- Milford M, Wyeth G, (2008) Mapping a suburb with a single camera using a biologically inspired SLAM system, IEEE Transactions on Robotics, 24 (5) p1038
QUT ePrints
For more publications by Michael, explore their research in QUT ePrints (our digital repository).
Awards
- 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.
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
- ARC Industrial Transformation Training Centre for Joint Biomechanics
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- IC190100020
- Start year
- 2020
- Keywords
Supervision
Current supervisions
- Insect brain-inspired learning algorithms for visual place recognition
PhD, Principal Supervisor
Other supervisors: Distinguished Professor Peter Corke - Appearance and Viewpoint Invariant Visual Place Recognition using Multi-scale and Multi-modality Systems
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 - 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, Professor Felipe Gonzalez - Simulation for Robot Vision
PhD, Associate Supervisor
Other supervisors: Distinguished Professor Peter Corke - UAV Navigation using Semantic Cues
PhD, Associate Supervisor
Other supervisors: Professor Felipe Gonzalez
Completed supervisions (Doctorate)
- 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)