Shenghua He

Shenghua Shenghua possesses extensive experience as an applied scientist, with a focus on large language models (LLMs) and computer vision. At Amazon, from December 2021 to April 2025, Shenghua led research in reinforcement learning for LLMs and developed an evaluation methodology for LLM-as-a-judge methods, which was accepted at the ICLR 2025 workshop. Additionally, Shenghua worked on 3D Multi-Object Tracking (MOT) from surveillance videos, notably creating the PieTracker algorithm that achieved third place in the CPVR2022 MOT challenge. Prior experience includes serving as a senior research scientist at PAII and a visiting scholar at the University of Illinois Urbana-Champaign, focusing on medical image analysis. Academic credentials include a PhD in Computer Science from Washington University in St. Louis and a Master's degree in Electrical, Electronics, and Communications Engineering from Beijing University of Posts and Telecommunications.