Qiyue Deng

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About

Qiyue Deng investigates the neural and behavioral mechanisms underlying predator-prey interactions, with a focus on how rodents learn and refine pursuit strategies through confrontation. His work bridges ethology and computational modeling, offering novel insights into survival-driven behavior. Deng’s 2024 study introduced a method for studying escape behavior to terrestrial threats in rodents, establishing a foundational framework for controlled laboratory experiments. His 2025 paper presents PursuitNet, a deep learning model that predicts competitive pursuit-like behavior in mice, outperforming existing models like Social GAN and TUTR in trajectory prediction. The model uses the PEC dataset, which captures real-time pursuit-escape behavior with abrupt speed changes, enabling dynamic predator–prey interaction modeling. Deng also demonstrated that confrontation experience against escaping bait improves pursuit strategy in mice, showing that repeated encounters refine motor and decision-making skills. Though early in his career, his work has already garnered citations and is shaping research in computational ethology and behavioral neuroscience. His integration of deep learning with traditional behavioral assays marks a significant step toward understanding the evolution of survival strategies.