College of Science & Engineering
Sophia Love
- Doctor of Philosophy (Natural and Physical Sciences)
- sophie.love@jcu.edu.au
Elle Robertson
- Doctor of Philosophy (Agriculture, Environmental and Related Studies)
- elle.robertson@jcu.edu.au
Romain Vaucher
- Senior Lecturer, Sedimentology
- romain.vaucher@jcu.edu.au
Jenny Fisher
- Associate Dean, Learning and Teaching
- jenny.fisher@jcu.edu.au
Ambili Narayanan
- Doctor of Philosophy (Natural and Physical Sciences)
- ambili.narayanan@my.jcu.edu.au
Sarfaraz Ali
- Postdoctoral Research Fellow
- sarfaraz.ali@jcu.edu.au
Mikaeylah Davidson
- Postdoctoral Research Fellow
- mikaeylah.davidson@jcu.edu.au
Liuxin Chen
- Lecturer
- liuxin.chen@jcu.edu.au
Rafael Cabral Carvalho
- Lecturer, Marine Geoscience
- rafael.cabralcarvalho@jcu.edu.au
Tom Lloyd
- Postdoctoral Research Fellow, Global Ecosystems
- tom.lloyd@jcu.edu.au
Internet of Things and Big Data Analytics for Cairns Marine (Old ID 26460)
This project will assist to analyse the large repository of data held by Cairns marine in relation to its full operations, i.e., from harvest to husbandry, inventory tracking and sales fulfilment. The physical systems currently in use at Cairns Marine are extensive and complex, involving a range of activities in Northern Australia, all activities on site (including R&D) in Cairns and full product (marine animals) stewardship to destination. A deep and informed understanding of data is required by the business to meet its growing global product commitments.
Internet of Things and Big Data Analytics for Cairns Marine (Old ID 26460)
This project will assist to analyse the large repository of data held by Cairns marine in relation to its full operations, i.e., from harvest to husbandry, inventory tracking and sales fulfilment. The physical systems currently in use at Cairns Marine are extensive and complex, involving a range of activities in Northern Australia, all activities on site (including R&D) in Cairns and full product (marine animals) stewardship to destination. A deep and informed understanding of data is required by the business to meet its growing global product commitments.
Comparing the use of underwater video and unmanned aerial vehicles for assessing use of tropical estuaries by marine fauna (Old ID 27583)
Remote underwater video (RUV) is considered an established method for elucidating fish community structure but little work has been done to assess the optimal number of cameras required to precisely assess species richness. Unmanned aerial vehicles (UAVs), on the other hand have remained completely untested for this purpose. Using the two methods in tandem (RUVs and UAVs), this project aims to compare established (RUV) and novel (UAV) methodologies for determining fish community structure and determine how may cameras are required to accurately and precisely assess the use of large woody debris by fish.
NESP 3.4 Better management of catchment runoff to marine receiving environments in northern Australia. (Old ID 28969)
Runoff from catchments in northern Australia has the potential to carry large amounts of sediment and nutrients. These available nutrients are important in driving coastal and estuary productivity, including many commercially and recreationally targeted species. Water resource development in northern Australia could reduce the supply of freshwater flow to the coast, thereby limiting supply of nutrients. This research project will examine the potential risks water resource development presents to Gilbert (QLD), Daly (NT) and Ord (WA) marine and coastal areas. We will complete a literature review, undertake flood plume modelling and examine vegetation damage along these coastal areas.
Genomic tools for monitoring yellow crazy ants. (Old ID 29026)
This project will establish protocols and baseline data for ddRAD-seq based sequencing of yellow crazy ants. In this phase of the project, we will sequence 200 individuals from historical infestations and develop tools to assess genetic relatedness among infestations. Baseline data established in this project will be used to help trace the origin of future infestations as well as improve our understanding of genetic diversity and gene flow in yellow crazy ants in Queensland.
Genomic tools for monitoring yellow crazy ants. (Old ID 29026)
This project will establish protocols and baseline data for ddRAD-seq based sequencing of yellow crazy ants. In this phase of the project, we will sequence 200 individuals from historical infestations and develop tools to assess genetic relatedness among infestations. Baseline data established in this project will be used to help trace the origin of future infestations as well as improve our understanding of genetic diversity and gene flow in yellow crazy ants in Queensland.
From Coastal Communities to Cloud Communities – New Application and Artificial Intelligence to Monitor Fish Stocks Using Photos – Application Development (Old ID 26805)
The Project aims at develop an artificial intelligence capable to autonomously identify fish species and number from images collected at fish markets in remote location, so that effective catch rate can be evaluated and management policies can be developed.
From Coastal Communities to Cloud Communities – New Application and Artificial Intelligence to Monitor Fish Stocks Using Photos – Application Development (Old ID 26805)
The Project aims at develop an artificial intelligence capable to autonomously identify fish species and number from images collected at fish markets in remote location, so that effective catch rate can be evaluated and management policies can be developed.
Do Melomys cervinipes have personalities? Variations in behaviour and hormones (Old ID 22230)
Behavioural syndromes or personalities are a series of correlated behaviours that are consistently displayed within an environment by an individual. I aim to study whether the fawn-footed melomys, Melomys cervinipes, in the Wet Tropics has distinct behavioural syndromes and whether these behavioural syndromes are associated with habitat disturbance. I hypothesise that individual M. cervinipes will show distinct behavioural syndromes depending on their habitat. This study will provide a greater understanding of the relationship between behavioural syndromes and habitat disturbance in a poorly studied Australian rodent. This knowledge will provide an insight into how individual and population fitness could be affected in degraded environments and how animals may cope with environmental change.
Identification of benthic structure using machine learning (Old ID 26732)
The Project aims at automating the classification of benthic structure and biota from images using machine learning
Site characterisation for residential slabs and footings - Australian practice
- 2020
- Taylor & Francis
- Researchers:Siva Sivakugan
Pan-cancer analysis of whole genomes
- 2020
- Nature Publishing Group
- Researchers:Matt Field
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01 Jan 2025
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01 Jan 2022
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01 Jan 2020
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01 Jan 2025
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01 Jan 2024
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01 Jan 2024
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01 Jan 2022