Fanyou Wu

Fanyou Wu's work spans two connected areas: applying large language models (LLMs) to dialogue systems, topic modeling, and safety/reasoning issues, and using machine learning (including deep reinforcement learning) for transportation problems like vehicle dispatching and travel behavior prediction. Recent work concentrates on making LLMs safer and more reliable for conversational and business applications, such as reducing hallucination and bias, while earlier work applied AI methods to urban transportation and logistics challenges.

Publication output has grown from occasional papers in the late 2010s to a steadier pace of 3-6 per year since 2021, with a peak in 2023 and continued activity through 2025.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026