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💻 Hi there! I am a Full-Stack Data Engineer, Data Scientist, and AI Integration Specialist with 3+ years of hands-on experience building end-to-end data solutions, intelligent automation systems, scalable web applications, and real-time machine learning products. My journey began in data extraction and web scraping, where I developed advanced scraping systems for e-commerce platforms, business intelligence, market research, and large-scale data collection. Over time, I expanded into full-stack data engineering, cloud deployment, AI integration, and production-grade application development, helping businesses transform raw data into live, intelligent products. I have worked as a Statistics Data Labeler at MathGPT.ai, Data Analyst, Business Analyst, and AI Research Intern at the Key Laboratory of Artificial Intelligence, OPTICS & Electronics (iOPEN), Xi’an, China. My background combines academic research, software engineering, machine learning, and business-focused problem-solving. Today, I specialize in building complete data ecosystems from research and data acquisition to automated pipelines, cloud infrastructure, databases, web applications, AI agents, and real-time analytics platforms. 🚀 What I Offer 🌐 Data Extraction & Web Scraping Advanced web scraping and data extraction E-commerce scraping (variants, pricing, reviews, shipping, specifications) JavaScript-heavy website scraping API integration and reverse-engineering Large-scale crawling and data collection systems Lead generation and market intelligence Automated data acquisition pipelines ⚙️ Data Engineering & Automation End-to-end ETL/ELT pipeline development Automated data workflows and scheduling PostgreSQL database design and optimization Real-time data processing systems Data warehousing and migration Cloud-based data infrastructure Workflow automation and monitoring 💻 Full-Stack Development & Deployment Data-driven web applications Dashboard and analytics platforms Backend API development Frontend integration with live databases Vercel, Netlify, Cloudflare deployment Azure and Contabo server deployment Production-ready application architecture Scalable cloud infrastructure 🤖 AI Integration & Machine Learning OpenAI GPT integration DeepSeek API integration AI chatbots and AI assistants Custom AI-powered web applications Machine learning model deployment Real-time prediction systems Predictive analytics and forecasting Fine-tuned AI solutions for business workflows 📊 Data Science & Analytics Exploratory Data Analysis (EDA) Statistical analysis and hypothesis testing Time series forecasting Predictive modeling and classification Business intelligence reporting KPI development and performance analysis Outlier detection and anomaly analysis Data visualization and decision-support systems 🛠 Tools & Technologies Python | PostgreSQL | SQL | Pandas | NumPy | Scikit-Learn | TensorFlow | PyTorch | XGBoost | LightGBM | R Programming | MATLAB Selenium | Scrapy | BeautifulSoup | Playwright | Requests | APIs | JSON/XML Parsing | Data Pipelines | ETL/ELT | Automation Systems OpenAI GPT | DeepSeek | AI Agents | Chatbots | LLM Integrations | Machine Learning Deployment PostgreSQL | Supabase | Render | Azure | Vercel | Netlify | Cloudflare | Contabo | Linux Servers Power BI | Tableau | Excel | Google Sheets | Data Visualization | Statistical Analysis | Business Analytics 📚 Portfolio Highlights • End-to-End Data Platforms – Built complete data ecosystems from collection to deployment for multiple businesses • Smart E-Commerce Scrapers – Automated extraction of variants, pricing, shipping, reviews, and product specifications • Real-Time Data Applications – Live systems that continuously collect, process, analyze, and display data • AI-Powered Business Solutions – Integrated GPT and DeepSeek-powered assistants into production websites • PyGWML Package – Open-source Python package for Geographically Weighted Machine Learning • EEG Microstate Classification – Brain state classification research in collaboration with academic institutions • Climatic Trend Forecasting – Advanced time-series forecasting and urban climate analysis 🌟 Why Work With Me? ✅ Full End-to-End Solution Provider – From research and data collection to deployment and AI integration ✅ Strong Background in Data Science, Data Engineering, and Software Development ✅ Experience Building Production-Ready Systems Used by Real Businesses ✅ Expertise in Automation, Cloud Infrastructure, and Real-Time Applications ✅ DataCamp Certified in Data Science & Web Scraping ✅ Excellent Communication and Client Collaboration ✅ Committed to Clean Code, Scalability, and Long-Term Maintainability 💡 Let's Build Something Powerful Whether you need advanced web scraping, automated data pipelines, AI-powered applications, cloud deployment, machine learning solutions, or complete end-to-end data platforms, I can help turn your idea into a reliable, scalable product. 📩 Lets Connect!

I am a Ph.D. student and AI researcher with a strong focus on deep learning, computational neuroscience, and Large Language Models (LLMs). Working daily in a high-paced research lab, I specialize in transforming raw data into reproducible, high-performing machine learning pipelines. Whether it's fine-tuning LLMs for specific downstream tasks or building complex computer vision models, I bring rigorous academic standards and engineering best practices to every project. Core Tech Stack & Skills: Deep Learning Frameworks: PyTorch (Primary), TensorFlow, Keras. LLMs & NLP: Model fine-tuning (LoRA, PEFT, Hugging Face transformers), sequence classification, and prompt optimization. Computer Vision & Medical AI: 3D/2D CNNs, Vision Transformers (ViTs), U-Net architectures, and neuroimaging (MRI) analysis using MONAI, SimpleITK, and nibabel. Data Science & MLOps: Python, Pandas, NumPy, Scikit-learn. Experiment tracking (W&B, TensorBoard), version control (Git), and environment management (Docker, Conda, Linux)

I build ML and AI systems that ship — and I design the evaluation and experiments to prove they work in production. My work spans recommendation systems, forecasting, churn and ETA prediction, and more recently LLM applications including RAG and AI agents. 11 years of production ML at Meituan, Didi, and LINEMAN (Thailand's largest food-delivery platform). Recent results: • Delivery-time (ETA) model — XGBoost with quantile loss, cut long-tail MAE by 6.8% (A/B tested) • Multi-objective ranking (MMoE) + DPP re-ranking for a B2B marketplace — +3.87% GMV per user, +6.53% CTR • RAG question-answering system over 10,000+ company financial reports — embeddings + FAISS + LLM What I can build for you: • LLM apps & RAG: document Q&A and chatbots grounded in your own data (OpenAI / Anthropic / open-source models, FastAPI backends, vector search), with an eval set so you know it works • AI agents & workflow automation: tool-calling agents, structured output, guardrails • Forecasting & predictive modeling: demand, ETA, churn — explainable and A/B-tested • Recommendation systems: retrieval + ranking + re-ranking, cold start, latency budgets Stack: Python, SQL, PyTorch, Spark, FastAPI, LangChain, AWS SageMaker. Based in UTC+8 — I overlap US mornings and EU afternoons.

I build and evaluate production AI agents for real business workflows. I work from ambiguous requirements through architecture, implementation, evaluation, deployment, observability, and handoff. Recent delivery: I completed Kinetix Mentor through a $5,600 / 140-hour Upwork engagement. It is a deployed WhatsApp AI platform combining Gemini models, LangGraph orchestration, Pinecone RAG, PostgreSQL memory, multimodal processing with GCS, Stripe subscriptions, external research tools, LangSmith tracing, FastAPI, and Docker. The client gave the project 5 stars and described me as “a complete professional who gets the job done.” I am now turning Kinetix into a measurable Agent Evaluation system. Current work includes: • Versioned JSONL evaluation datasets and repeatable model runners • Deterministic scoring for tool selection, routing, arguments, security, and response contracts • Repeated live-model evaluation instead of one-off testing • Trace-driven failure analysis and targeted regression testing • Separation of scorer defects, agent defects, and infrastructure failures The first router baseline evaluated 30 repeated model runs, uncovered both measurement defects and genuine agent failures, and produced a 17/17 passing targeted regression after fixes. I can help you: • Build or repair LangGraph, RAG, and tool-using AI agents • Create evaluation datasets, behavioral scorers, and regression suites • Diagnose production traces and improve reliability, quality, latency, and cost • Integrate FastAPI, PostgreSQL, vector databases, webhooks, payments, and external APIs • Turn an AI prototype into a deployed, observable workflow with clear documentation and handoff Before freelancing, I worked in ByteDance’s international business, building data-driven systems and translating ambiguous business problems into measurable technical outcomes. Best fit: AI Agent and RAG systems, LLM evaluation, existing AI product improvements, reliability audits, and production integrations. Send me your workflow, current architecture, failure examples, and success criteria. I’ll propose a concrete first milestone.