I am an Applied Scientist at Amazon working on customer-facing Agentic systems. My interests include post-training, agents, personalization, RAG, and long-context modeling. I received my Ph.D. in Computer Science from Texas A&M University.
Email: chenpei.net@gmail.com
Links: GitHub
LinkedIn
Google Scholar
Office: Santa Clara, CA
Ph.D. in Computer Science, 2019 -
Texas A&M University
MS in Finance, 2016 - 2018
Southwestern University of Finance and Economics
B.Eng. in Simulation Engineering, 2010 - 2014
National University of Defense Technology
HYTREL: Hypergraph-enhanced Tabular Data Representation Learning
Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, et al.
NeurIPS 2023, Spotlight (top 5%)
Mosaic-IT: Cost-Free Compositional Data Synthesis for Instruction Tuning
Ming Li, Pei Chen, Chenguang Wang, Hongyu Zhao, Yijun Liang, et al.
ACL 2025, Findings
ItD: Large Language Models Can Teach Themselves Induction through Deduction
Wangtao Sun, Haotian Xu, Xuanqing Yu, Pei Chen, Shizhu He, et al.
ACL 2024, long paper
Aligning Large Language Models with Implicit Preferences from User-Generated Content
Zhaoxuan Tan, Zheng Li, Tianyi Liu, Haodong Wang, Pei Chen, et al.
ACL 2025, long paper
CoMM: Collaborative Multi-Agent, Multi-Reasoning-Path Prompting for Complex Problem Solving
Pei Chen, Shuai Zhang, Boran Han
NAACL 2024, Findings
Hephaestus: Improving Fundamental Agent Capabilities of LLMs through Continual Pre-Training
Yuchen Zhuang, Jingfeng Yang, Haoming Jiang, Xin Liu, Pei Chen, et al.
NAACL 2025, long paper
Improving LLMs Function Calling and Interpretability via Guided-Structured Templates
Hy Dang, Tianyi Liu, Zhuofeng Wu, Jingfeng Yang, Pei Chen, et al.
EMNLP 2025, long paper
LongLeader: A Comprehensive Leaderboard for LLMs in Long-context Scenarios
Pei Chen, Hongye Jin, Cheng-Che Lee, Rulin Shao, Jingfeng Yang, et al.
NAACL 2025, long paper
ALERT: An LLM-powered Benchmark for Automatic Evaluation of Recommendation Explanations
Yichuan Li, Xinyang Zhang, Chenwei Zhang, Mao Li, Pei Chen, et al.
NAACL 2025, long paper
UniConv: Unifying Retrieval and Response Generation for LLMs in Conversations
Fengran Mo, Yifan Gao, Chuan Meng, Xin Liu, Pei Chen, et al.
ACL 2025, long paper
๐ฌ By day: a creative and hands-on LLM scientist with a strong research mindset and a builder’s instinct, excited by bold new ideas in LLMs, AI assistants, and agentic systems. Enjoys exploring emerging directions and turning them into practical solutions for real-world industry problems.
๐ป By night: a geek who reads papers for fun, tinkers with side projects, and has strong opinions about post-training recipes.
๐ฅ On weekends: 1st DAN in ITF Taekwon-Do, active in swimming, badminton, and boxing โ because the best debugging happens after a good workout.