I work on problems in wildlife conservation and environmental science using big data with high structural complexity (e.g., wildlife imagery data, accelerometer data, and audio data) and state-of-the-art artificial intelligence methods (e.g., computer vision and deep learning). The goal is to address large-scale environmental issues that are not achievable with conventional ecological methods and monitor species responses to climate changes. My research also serves as a bridge between applied computer / data science and ecological / environmental research.

My primary responsibilities within the group include:

• The development of algorithms for automatic fish recognition through echosounder imagery