HLHaloLab

Front-End · Applied AI · Product Delivery

首屏加载 检测中...

Haolong浩龙

M.Eng Candidate @ Shihezi University · Former Engineering Intern, Digital Corps

Front-end and applied AI engineer delivering web platforms and LLM-enabled workflows from discovery to production.

Focuses on React platform engineering, applied AI tooling, and cross-team collaboration that keeps experiments ship-ready.

PDF · English & 中文双语

Education 教育背景

Academic grounding in software engineering and cyberspace security informs an engineering-first approach to product delivery.

  • Shihezi University | College of Cyberspace Security

    M.Eng - Cyberspace Security

    2023.09 - 2026.06Top 10% GPA

  • Henan University | Software College

    B.Eng - Software Engineering

    2018.09 - 2022.06Top 10% GPA

Technical Stack 技能矩阵

Tooling selected by delivery impact and depth of ownership.

Front-End Core

  • TypeScript
  • React 19 (Hooks & Router 7)
  • Vite 7
  • Ant Design
  • CSS Modules
  • Axios SDK abstraction

AI & LLM Tooling

  • RAG (FAISS + BM25)
  • LangChain prompt/retrieval chains
  • FastAPI + SSE streaming
  • Ollama
  • sentence-transformers embeddings

Full-Stack & Observability

  • Node.js & Express
  • PostgreSQL
  • Docker
  • GitHub Actions
  • WebVitals (FCP/CLS)
  • ErrorBoundary + sourcemap reporting

Experience 实习经历

Bridging LLM safety, knowledge engineering, and performance operations in a national digital transformation initiative.

2024.12 - 2025.06
  • Designed MCP tool-calling guardrails so LLM agents could execute SSH/SFTP safely with auditable trails.
  • Curated enterprise knowledge assets and an evaluation set to benchmark RAG retrieval quality.
  • Implemented route-level code splitting, WebVitals instrumentation, and sourcemap triage pipelines.

Digital Corps | National Digital Transformation Program

Product Engineering Intern · Urumqi, China

Projects 项目实践

Selected builds demonstrating engineering depth and applied AI impact.

2025.06 - Present
  • Refactored a multi-module front-end (Todo / Markdown / Gacha / FrameStats) with code splitting and shared API clients.
  • Established Route-Controller-Service-Model layering and error telemetry for traceable incidents.
  • Built data visualisations fed by GitHub and NPM APIs to evaluate experiments and demos quickly.

HaloLab | Engineering Visualisation Platform

React 19 + Vite 7 | Node.js + Express | PostgreSQL

2025.05 - Present
  • Automated document ingestion pipelines with semantic chunking and embedding generation for FAISS stores.
  • Blended dense retrieval with BM25 reranking and templated prompts for reliable grounded answers.
  • Delivered streaming SSE responses with citation highlighting plus latency and cost diagnostics.

QwenLocalRAG | Knowledge Retrieval Toolkit

LangChain | FAISS | BM25 rerank | FastAPI | Vue / SSE

2024.09 - 2024.12
  • Curated rumor datasets under imbalanced settings and engineered linguistic plus propagation features.
  • Benchmarked classical models alongside BERT fine-tuning with event-based splits for fair comparison.
  • Produced reusable evaluation scripts (Macro-F1 | ROC-AUC) and an error taxonomy for future warning systems.

Wisdom Rumor Analysis | Competition Toolkit

PyTorch | BERT fine-tuning | SVM / Logistic baselines

Honors & Publications 荣誉与发表

Recognition for applied AI innovation and academic research.

Honors

  • Xinjiang Digital Economy Innovation Summit | Autonomous Region First Prize (2025)
  • China Mobile Wutong Cup Data Innovation Contest | National Excellence Award (2024)
  • Blue Bridge Cup Graduate Division | Provincial Third Prize (2024)
  • National Collegiate Computing Ability Challenge | Northwest Region Second Prize (2023)

Publications & Community

  • Cluster Computing (JCR Q1): HASBFT - A Byzantine Fault-Tolerant Consensus Algorithm with transaction hash compression and aggregated signature optimisation.
  • CSDN Creator @haolong | 290K+ reads | https://haolong.blog.csdn.net

Foundations 基础能力补充

  • Strong CS fundamentals across data structures, networks, architecture, and operating systems.
  • Deep JavaScript/TypeScript expertise, dual-stack React/Vue practice, and Webpack/Vite build fluency.
  • TensorFlow/PyTorch training with front-end deployment (TensorFlow.js) plus practical AIGC integration.
  • Comfortable with Linux and Git workflows, distributed systems concepts, and Docker-based delivery.
  • Experience with Jest, front-end performance profiling, and LLM interaction design for production apps.
© 2025 HaloLab|豫ICP备2025148471号-1