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jiawei Li

Intern Applied Scientist specializing in LLM agents for software engineering

AmazonUC Irvine0 Years ExperienceIntern LevelWorks On-Site

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About

Applied Scientist intern at Amazon who built a production-adopted LLM-judge to evaluate an agentic chatbot’s intermediate reasoning and tool calls using a knowledge-graph grounding approach. Also published award-winning work (ACM SIGSOFT Distinguished Paper) using LangChain + GPT-4 tools to generate factually grounded commit messages, with rigorous human-centered evaluation metrics.

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Key Strengths

  • Built and deployed an LLM-judge system adopted by Amazon team for periodic chatbot evaluation
  • Knowledge-graph-based validation of intermediate reasoning steps and tool calls for agentic chatbots
  • Designed heuristic for query ambiguity using LLM confidence; validated via correlation analysis with human experts
  • Hands-on orchestration experience (LangChain/LangGraph/AutoGen) for LLM agents and multi-agent systems
  • ACM SIGSOFT Distinguished Paper Award for LangChain-based GPT-4 tool-using commit message generation
  • Strong evaluation mindset: combines human metrics, factual grounding checks, and latency/LLM-call cost considerations
  • Effective communication with non-technical stakeholders using latency data and concrete LLM output examples

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Experience

Applied Scientist InternAmazon Inc. · Jun 2025 – Sep 2025internship

Education

UC Irvinedoctorate, Software Engineering (2026)
UC Irvinemaster, Computer Science (2020)
Xi'an Jiaotong Universitybachelor, Software Engineering (2019)

Awards

  • ACM SIGSOFT Distinguished Paper Award (FSE 2024)

Skills

PythonJavaRPyTorchScikit-LearnXGBoostMachine LearningSupervised LearningDeep LearningLarge Language Models (LLMs)GPT-4Prompt engineeringAgentic AIMulti-agent systemsLangChain

Languages

English

Publications

14 publications

Large Language Models for software engineeringAgentic AI and prompting techniquesCommit message generation and quality evaluationCode review automationAI-generated code detectionProgram repair and multimodal inputsTest smells and software testing qualityDefect prediction and bias in ML systemsCode generation mistakes and fine-tuning

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jiawei LiIntern Applied Scientist specializing in LLM agents for software engineering