The Mississippi River relies on dams for commercial navigation, but these structures block fish migration and damage ecosystems and local fishing economies. This research uses hydrodynamic modelling to test fish-passage designs, such as bypass channels, showing how they can reconnect habitats, support biodiversity, and allow economic and ecological goals to coexist.

My research uses artificial intelligence to detect water pollution by analysing DNA traces left by aquatic species. Instead of relying on visual signs or costly expert identification, supervised machine learning reads species patterns to determine water quality. The method is faster, cheaper, and more accurate than traditional analysis.

This research investigates how Amazonian butterflies evolve their visual systems to match the light conditions of different rainforest niches. By comparing eye and brain structures across many species, it reveals that evolution repeatedly finds the same sensory solutions, showing that adaptation can be surprisingly predictable and may drive the formation of new species.

This research studies the unusually long-lived Heliconius butterflies to uncover genetic mechanisms behind extended lifespan. By analysing DNA from butterflies across their lifespan, it aims to reveal evolutionary strategies for longevity that may inform future human ageing therapies. Understanding diverse animal lifespans could guide healthier ageing — without mythical “Fountains of Youth.”