Overview
Background
I am an applied mathematcian, using mathematics to improve decision-making outcomes for biodiversity conservation and epidemics management. My primary expertise lies in Partially Observable Markov Decision Processes and the Value of Information, and have research interestest in Operations Research, Data Science and Artificial Intelligence.
I am in ECR Representative for the Centre for Biodiversity and Conservation Science, currently organising the weekly seminars for the centre.
I completed my PhD at the Queensland University of Technology, designing optimization approaches for biodiversity conservation using new technologies.
Availability
- Dr Luz Pascal is:
- Not available for supervision
Qualifications
- Masters (Research) of Applied Mathematics, Institut Polytechnique de Paris
- Doctor of Philosophy of Mathematics, Queensland University of Technology
Works
Search Professor Luz Pascal’s works on UQ eSpace
2025
Journal Article
Developing new technologies to protect ecosystems: planning with adaptive management
Pascal, Luz Valerie, Chadès, Iadine, Adams, Matthew P. and Helmstedt, Kate J. (2025). Developing new technologies to protect ecosystems: planning with adaptive management. Proceedings of the National Academy of Sciences, 122 (39) e2422002122, 1-10. doi: 10.1073/pnas.2422002122
2025
Journal Article
EEMtoolbox: A user-friendly R package for flexible ensemble ecosystem modelling
Pascal, Luz Valerie, Vollert, Sarah A., Bimler, Malyon D., Baker, Christopher M., Vernet, Maude, Canessa, Stefano, Drovandi, Christopher and Adams, Matthew P. (2025). EEMtoolbox: A user-friendly R package for flexible ensemble ecosystem modelling. Methods in Ecology and Evolution, 16 (5), 921-929. doi: 10.1111/2041-210X.70032
2021
Journal Article
A primer on partially observable Markov decision processes (POMDPs)
Chadès, Iadine, Pascal, Luz V., Nicol, Sam, Fletcher, Cameron S. and Ferrer‐Mestres, Jonathan (2021). A primer on partially observable Markov decision processes (POMDPs). Methods in Ecology and Evolution, 12 (11), 2058-2072. doi: 10.1111/2041-210x.13692
2020
Journal Article
A Shiny <scp>r</scp> app to solve the problem of when to stop managing or surveying species under imperfect detection
Pascal, Luz, Memarzadeh, Milad, Boettiger, Carl, Lloyd, Hannah and Chadès, Iadine (2020). A Shiny r app to solve the problem of when to stop managing or surveying species under imperfect detection. Methods in Ecology and Evolution, 11 (12), 1707-1715. doi: 10.1111/2041-210x.13501
Media
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