秀色短视频

Presenter: Dania Tamayo-Vera, candidate for a tenure-track position in the School of Mathematical and Computational Sciences

Teaching talk: Monday, April 22, 9:30--10:20 am, Cass Science Hall 101

Research talk: Monday, April 22, 1:45--2:45 pm, Cass Science Hall 101

Title: "Adapting an Automated Machine Learning System to Enhance Research Replicability and Accessibility in Agroclimatic Studies"

Abstract: 

The urgency of climate change calls for innovative solutions across disciplines, particularly through the democratization of machine learning (ML) technologies in environmental sciences. My research trajectory began with the application of ML in cryptography and security, which has now shifted towards utilizing ML to predict and assess the impacts of climate change in various sectors.

A review of ML and deep learning (DL) applications in agriculture revealed a critical need for well-documented methodologies to improve research reproducibility and accessibility. My current research focuses on the introduction and development of an Automated Machine Learning (AutoML) system designed to enhance the replicability of ML applications in agroclimatic research. As a result, this research is promoting innovation in agricultural practices tailored for climate mitigation and adaptation.

Looking ahead, my research will integrate additional scenarios such as market dynamics and decision-making processes affecting agriculture. Prince Edward Island (PEI), an area suffering from climate-related challenges, serves as an ideal place for testing and advancing these technologies. While PEI has the potential to be the birthplace of these technologies, global technology sharing is crucial to ensure equitable distribution, especially in areas that are most prone to climate challenges. Supporting technology development and distribution is a way to combat climate change and injustice and promote global resilience.

Teaching and research talks are open to the 秀色短视频 campus community.