Dr Cheryl McCarthy is an Associate Professor in mechatronic engineering with the Centre for Agricultural Engineering at the University of Southern Queensland. She has been a full-time researcher on industry projects since 2009. Her research involves developing machine vision and sensing systems for terrestrial farming, and for space agriculture. She has led machine vision projects for the beef, poultry, cotton and sugar industries and her current projects include machine vision sensing of meat chickens for weight and welfare detection, with AgriFutures Australia, and a plant monitoring payload for the International Space Station, with the iLAuNCH Trailblazer. She has a BEng (Mechatronic) and PhD from UniSQ. Her research interests include the application of mechatronic engineering to agriculture, visual and non-visual image signal processing, and software user experience. She holds a CASA Remotely Piloted Aircraft Operator's Certificate.

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Projects - current:

* Plant health monitoring payload for ISS (iLAuNCH Trailblazer, 2025-2027)

* TRL8: Novel detection of chicken welfare Phase 3 (AgriFutures Chicken Meat Program, 2024-2026)

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Projects - completed: Space agriculture

* Machine vision for food plant safety in space (Australian Space Agency Moon to Mars Demonstrator, 2021-2022)

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Projects - completed: Terrestrial agriculture - livestock

* Farm trials for machine vision of chicken welfare Phase 2 (AgriFutures Chicken Meat Program, 2022-2023)

* Hen health status with machine vision (Australian Eggs, 2022-2023)

* Feasibility of induction automation R&D (Meat and Livestock Australia, 2018)

* Novel detection of chicken welfare with machine vision Phase 1 (AgriFutures Chicken Meat Program, 2017-2021)

* Automation opportunities in beef feedlot induction (Meat and Livestock Australia, 2017)

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Projects - completed: Terrestrial agriculture - cropping

* Detection of sugar cane harvester losses with machine vision (Sugar Research Australia, 2019-2021)

* Statement of Works (John Deere, 2017-2018)

* Field ready, optimised precision weed identification sensor system (Sugar Research Australia, 2016-2019)

* RPAS (UAV) automated surveillance of crop hotspots for improved management (Queensland Government Accelerate Fellowship, 2014-2017)

* Commercial development and evaluation of a machine vision-based weed spot sprayer (CRDC, 2013-2016)

* Precision weed sensing for pyrethrum (HIA, 2012-2016)

* Deployment and refinement of bait box remote surveillance system (HIA/RIRDC, 2013-2014)

* Remote sensing of beehives to improve surveillance (HIA/RIRDC, 2011-2013)

* Precision sensing technology for infield identification of summer weeds (RIRDC, 2011-2012)