Researchers at Georgia Tech, led by Professor David Hu, have developed a model to predict mosquito behavior by analyzing their flight patterns in response to various stimuli. Initially, undergraduate Chris Zuo volunteered to be exposed to 100 disease-free mosquitoes in a controlled room, wearing only a mesh suit, which resulted in numerous bites. Subsequent experiments involved Zuo wearing unscented clothing and a mask, and later, a simple dummy emitting carbon dioxide and visual cues. Using the Photonic Sentry camera system, millions of mosquito flight trajectories were recorded and analyzed by mathematicians at MIT. The study revealed that visual targets elicit fly-bys, carbon dioxide causes "double takes," and the combination of both creates high-speed orbiting. This model was successfully tested by predicting mosquito distribution around Zuo, now acting as a "bull's-eye," and offers a more precise tool for designing mosquito capture and deterrence methods, aiming to combat the over 700,000 annual deaths caused by mosquito-borne diseases.