My research interests include Machine Learning, Natural Language Processing (NLP), Large Language Model, and Deep Learning. Especially at Amazon, I work on large language models (LLM) post-training including reasoning, planning, evaluation, and alignment.
I am always available for academic collaborations from academia and industry. Please feel free to contact me if you have research ideas or industry collaborations. I am more than happy to discuss and collaborate with you.
Selected Blogs
Bing He, Rui Sun, Zhan Shi, Building and Aligning LLM using User Data and RL, Blog link, November 2025
Bing He, Sreyashi Nag, Limeng Cui, Suhang Wang, Zheng Li, Rahul Goutam, Zhen Li and Haiyang Zhang, “Hierarchical Query Classification in E-commerce Search”, paper, ACM Web Conference (ACM WWW) 2024 (Acceptance Rate: 21.3%)
Bing He, Mustaque Ahamad, Srijan Kumar, “Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformation”, code and data, ACM Web Conference (ACM WWW) 2023 (Acceptance Rate: 365/1900=19.2%)
Bing He, Mustaque Ahamad, Srijan Kumar, “PETGEN: Personalized Text Generation Attack on Deep Sequence Embedding-based Classification Models”, code and data, ACM SIGKDD 2021 (Acceptance Rate: 238/1541=15.4%)
Internship Experiences
2023.05 - 2023.08: Amazon Search, Palo Alto, California
