Associate Professor

The petitioner proposes to utilize quantitative methods to study environmental mechanisms to advance scientific understanding of ecosystem dynamics and facilitate improved ecosystem management and conservation. Her work focuses on assessing the impact of local and landscape factors on plant and animal biodiversity to support global food accessibility and biodiversity preservation.

The petitioner proposes to continue developing mathematical and predictive models that assess how global environmental stressors impact natural ecosystems and biodiversity dynamics. His work focuses on modeling forest systems and analyzing species competition to forecast ecosystem shifts under climate variability. These models are intended to serve as tools for policymakers and conservationists to formulate effective responses to climate-driven disruptions.

The petitioner proposes to continue research on climate change impacts, invasive species, biocontrol, conservation, and ecosystem restoration. The work focuses on developing integrated and sustainable mathematical models and techniques for managing invasive species and pests to improve food biosecurity and protect coastal resources like coral reefs.

The petitioner proposes to continue developing machine learning and deep learning algorithms to improve real-time computer modeling for social and environmental artificial intelligence applications. The work specifically focuses on harnessing deep learning to support wildlife protection methods, including the classification of fish and birds for conservation management.