Tristan Perez and agbot crop.png


A professor in Robotics and Autonomous Systems will lead the Food Agility CRC’s Agri-food Informatics Research Program if the bid is successful. Professor Tristan Perez believes there is enormous potential for using information, extracted from purposefully collected data, to improve the management of agricultural production systems, to optimise yield, quality and efficiency whilst ensuring sustainability.

When in-farm and value-chain data are combined with systems mathematical models, novel statistical techniques and optimisation, key information can be extracted and be provided to farmers to enhance their management decisions. For a farmer, such decisions include aspects of crop planning, in season management, harvest and post harvest, as well as business.

Tristan Perez is Professor of Robotics and Autonomous Systems at the School of Electrical Engineering and Computer Science at Queensland University of Technology, QUT. He leads the IntelliSensing Enabling Platform at QUT’s Institute for Future Environments - a transdisciplinary research program aiming to assist industry and government to transition into the digital age by transforming data collection, modelling, analytics and decision making.


  • Dynamics and control of cyber-physical systems
  • Robotics with applications to agricultural automation
  • Bayesian inference and decisions under uncertainty
  • Agricultural cybernetics.

Tristan leads QUT developments in agricultural robotics, and is working with industry to develop decision support for crop management based on system-theoretic concepts - agricultural cybernetics.

Tristan is currently involved in the following research:

  • calibration of evapotranspiration crop models, based on global and local data
  • characterisation of uncertainty and loss functions for in-farm decisions
  • probabilistic assessment of robot behaviours to enable trusted autonomy
  • analytics for horticulture crop quality
  • frameworks for reducing the effect of cognitive inputs in rational decision making
  • vision systems for detection and classification of weeds
  • alternative methods for weed management enabled by robotics
  • robotic harvesting in horticulture.

Tristan is also Associate Investigator at the ARC Centre of Excellence for Robotic Vision, QUT, and also the ARC Centre of Excellence for Mathematical and Statistical Frontiers, at QUT.


Tristan brings a unique blend of leadership and technical capabilities to the Food Agility CRC - key to his leadership of the Agri-food Informatics Research Program. 

Over the past fifteen years, Tristan has been conducting trans-disciplinary research almost exclusively in collaboration with industry from several sectors including marine, aerospace, resources, econometrics and agriculture. This experience will be key for the leadership of the Agri-food Informatics Program and the development of partnerships with external stakeholders.

On the research capability side, Tristan’s experience in dynamical systems, decisions under uncertainty, cybernetics, robotics and autonomous systems brings a unique perspective to the design of data analytics in relation to management strategies for crop systems as well as the specification of digital infrastructure in relation to information needs for implementation of decisions in digital agriculture. Tristan has also been involved in research related to aspects of economics agricultural robotics as well as lego-regulatory frameworks.