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Associate Professor Michael Milford

Science and Engineering Faculty,
Electrical Engineering, Computer Science,
Robotics and Autonomous Systems

Personal

Name
Associate Professor Michael Milford
Position(s)
Future Fellow
Science and Engineering Faculty,
Electrical Engineering, Computer Science,
Robotics and Autonomous Systems
Associate Professor in Electrical Engineering
Science and Engineering Faculty,
Electrical Engineering, Computer Science,
Robotics and Autonomous Systems
Discipline *
Artificial Intelligence and Image Processing, Neurosciences
Phone
+61 7 3138 9969
Email
Location
View location details (QUT staff and student access only)
Social Media
LinkedIn
Qualifications

PhD (University of Queensland)

Professional memberships
and associations

IEEE Member ARAA Member. For more information please see my group research page https://wiki.qut.edu.au/display/cyphy/Michael+Milford or my Google Scholar page: http://scholar.google.com/citations?user=TDSmCKgAAAAJ&hl=en

Keywords

Robotics, Mapping, Navigation, Localization, Computational Neuroscience, RatSLAM, SeqSLAM, Hippocampus, Entorhinal Cortex

* Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2008

Biography

I am a leading robotics researcher conducting interdisciplinary research at the boundary between robotics, neuroscience and computer vision, and a multi-award winning educational entrepreneur. My research models the neural mechanisms in the brain underlying tasks like navigation and perception in order to develop new robotics and computer vision-related technologies, with a particular emphasis on challenging application domains where current techniques fail such as all-weather, anytime positioning for autonomous vehicles. I currently hold the position of Associate Professor at the Queensland University of Technology, as well as Australian Research Council Future Fellow, Microsoft Research Faculty Fellow and Chief Investigator on the Australian Centre for Robotic Vision.

My research has attracted more than twenty million dollars in research and industry funding, both in the form of sole investigator fellowships and large team grants. My papers have won (4) or been finalists (7) for 11 best paper awards including the 2012 Best Vision paper at ICRA2012. My citation h-index is 22, with 1882 citations as of July 11, 2016. I have given more than 30 invited presentations across ten countries at top international conferences, universities (including Harvard, MIT, CMU, Boston Uni, Cambridge and Imperial College London) and corporations (including Google and Microsoft).

As an educational entrepreneur, I have written and produced innovative textbooks for high school students for fifteen years, with more than 6000 physical sales and educational website and YouTube views in excess of 1.5 million. I am currently launching the company Math Thrills, an initiative combining mass market entertainment and STEM education. Math Thrills received pre-seed funding on Kickstarter ($2500) and seed funding ($50,000) from QUT Bluebox and is in initial school trials. The initiative has led to awards including the 2015 Queensland Young Tall Poppy of the Year Award and a 2015 TedXQUT talk.

I have dual citizenship between Australia and the United States, and have lived and worked in locations including Boston, USA and Edinburgh and London in the UK,  collaborating with organizations including Harvard University, Boston University, Oxford University, MIT, Edinburgh University, Imperial College London, Caterpillar, the US Air Force and NASA’s Jet Propulsion Laboratory.

This information has been contributed by Associate Professor Michael Milford.

Teaching

Teaching I teach ENB339 Introduction to Robotics in Semester 2 each year. In it we learn:

  • 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.
Videos
My academic YouTube channel Milfordrobotics has dozens of lectures, tutorials, and practical videos about robotics.
Teaching Grants
  • M. Milford, Small Teaching and Learning Grant, 2011-2012, “No Student Left Behind”, $5,500
This information has been contributed by Associate Professor Michael Milford.

Experience

I am a leading robotics researcher conducting interdisciplinary research at the boundary between robotics, neuroscience and computer vision, and a multi-award winning educational entrepreneur. My research models the neural mechanisms in the brain underlying tasks like navigation and perception in order to develop new robotics and computer vision-related technologies, with a particular emphasis on challenging application domains where current techniques fail such as all-weather, anytime positioning for autonomous vehicles. I currently hold the position of Associate Professor at the Queensland University of Technology, as well as Australian Research Council Future Fellow, Microsoft Research Faculty Fellow and Chief Investigator on the Australian Centre for Robotic Vision.

My research has attracted more than twenty million dollars in research and industry funding, both in the form of sole investigator fellowships and large team grants. My papers have won (4) or been finalists (7) for 11 best paper awards including the 2012 Best Vision paper at ICRA2012. My citation h-index is 22, with 1882 citations as of July 11, 2016. I have given more than 30 invited presentations across ten countries at top international conferences, universities (including Harvard, MIT, CMU, Boston Uni, Cambridge and Imperial College London) and corporations (including Google and Microsoft).

As an educational entrepreneur, I have written and produced innovative textbooks for high school students for fifteen years, with more than 6000 physical sales and educational website and YouTube views in excess of 1.5 million. I am currently launching the company Math Thrills, an initiative combining mass market entertainment and STEM education. Math Thrills received pre-seed funding on Kickstarter ($2500) and seed funding ($50,000) from QUT Bluebox and is in initial school trials. The initiative has led to awards including the 2015 Queensland Young Tall Poppy of the Year Award and a 2015 TedXQUT talk.

I have dual citizenship between Australia and the United States, and have lived and worked in locations including Boston, USA and Edinburgh and London in the UK,  collaborating with organizations including Harvard University, Boston University, Oxford University, MIT, Edinburgh University, Imperial College London, Caterpillar, the US Air Force and NASA’s Jet Propulsion Laboratory.

This information has been contributed by Associate Professor Michael Milford.

Publications


For more publications by this staff member, visit QUT ePrints, the University's research repository.

Awards

Awards and recognition

Type
Fellowships
Reference year
2013
Details
Microsoft Research Faculty Fellowship, $110,000
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
2013
Details
Best Paper Finalist "Towards Condition-Invariant, Top-Down Visual Place Recognition," Michael Milford, Walter Scheirer, Eleonora Vig and David Cox
Type
Membership of Review Panels on Prestigious Grant Applications
Reference year
2013
Details
Czech Science Foundation reviewer for Research Grants
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
2016
Details
Best Robot Vision Paper Award at the 2012 International Conference on Robotics and Automation
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
2012
Details
Canadian Natural Sciences and Engineering Research Council Reviewer for Discovery Grants
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
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

Grants and projects (Category 1: Australian Competitive Grants only)

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
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
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

Supervision