Jingzhi Lu

MSc Student (2025)

Project Title: The Taxonomic use of Artificial Intelligence for Identifying Caddisfly Larvae, based upon the Greenwood Collection

Research Focus: Jingzhi’s MSc research focuses on developing artificial intelligence approaches for the taxonomic identification of caddisfly larval fragments, in order to develop a method for identifying fragmented remains in river sediments. This work addresses the challenging task of larval identification in Trichoptera, which requires significant taxonomic expertise and is often a bottleneck in ecological and biodiversity studies.

Key Research Areas:

• Artificial intelligence in taxonomy
• Caddisfly (Trichoptera) larval identification
• Museum collection digitisation
• Automated species identification
• Machine learning applications in entomology

Research Significance: Caddisfly larvae are important indicators of freshwater ecosystem health, but their identification requires specialized knowledge that limits their use in biomonitoring and ecological research. Jingzhi’s work aims to democratize access to taxonomic expertise through AI-powered identification tools.