CV

AI researcher and engineer working on large language models, agent systems, and software engineering.

Education

GPA: 90.01/100 (3.8/4.0)

Research & Engineering Experience

• Worked on coding LLM post-training and evaluation, automated task construction, distributed agent execution, and repository-level code understanding.

• Developed retrieval-augmented code generation methods and multi-agent workflows for low-resource software libraries.

• Worked on LLM-based agent systems, model fine-tuning, knowledge graphs, and human-centered AI applications.

Selected Projects

RAGenius — Intelligent Knowledge Base System

• Designed a modular RAG pipeline incorporating hybrid retrieval, reranking, and context optimization.
• Implemented concurrent retrieval, caching, and streaming responses.
• Developed and deployed a full-stack application using React, FastAPI, Docker, and Nginx.
• Project: ragenius.xyz ↗

Publications

Conference Publication

TutorCraftEase: Enhancing Pedagogical Question Creation with Large Language Models
Wenhui Kang, Lin Zhang, Xiaolan Peng, Hao Zhang, Anchi Li, Mengyao Wang, Jin Huang, Feng Tian, and Guozhong Dai. ACM CHI 2025 (CCF-A). DOI ↗

Under Review

AdaptQuest: Adaptive Pedagogical Question Crafting Tool Driven by Knowledge Graph and Large Language Model
Manuscript under review.

Honors & Awards

• Mitacs Globalink Research Internship Award, 2025
• Academic Excellence Scholarship (Top 20%), Beijing University of Technology, 2023
• Innovation and Entrepreneurship Scholarship, Beijing University of Technology, 2023

Technical Skills