Heat stress, air pollution, and crop yield
Research
My academic research falls into three main areas:
Machine Learning Applications in the Atmospheric Environment
In this area, my research involves generating a global full-coverage ozone dataset using novel machine-learning methods. I also analyze anthropogenic influences on Earth and the resulting feedback to humans.
Impacts and Adaptations of the Human System to Climate Change
My main research agenda involves using advanced statistical models to establish relationships between a wide range of outcomes, such as crop yields and SIF, with climate and air pollution. These studies rely on publicly available data from remote sensing and numerical models.
Processes and Interactions Between Air Pollution and the Biosphere
I am interested in studying the complex interactions between air pollution and the biosphere. I use various techniques such as statistical learning, geospatial analysis, and big data to investigate the impacts of air pollution on ecosystems and the biosphere’s feedback to air pollution.
In a new avenue of research, I plan to use machine learning and big data to explore the interplay between human and nature.
