About me

I am a Software Engineer with a solid background in full-stack developent, machine learning, and cloud computing. I am passionate about building scalable and robust software systems and AI powered applications.

TechStack

  • Software Engineering

    Software Engineering

    Full-stack expert with focus on RESTful APIs, microservices, and database integration. Skilled in modern frontend and backend technologies for scalable solutions.

  • Machine Learning

    Machine Learning

    Proficient in CNN, RNN(GRU, LSTM), Transformer (BERT, GPT), GNN, RL (Q-Learning, DQN, PPO), GANs, LLMs, Stable Diffusion, RAG (Vector Database). Experienced with TensorFlow and PyTorch for deep learning.

  • Cloud Computing

    Cloud Computing

    Certified in AWS and Azure. Experienced in developing and deploying applications on AWS, Azure, and GCP.
    Cerificates: Azure AI Engineer, AWS Certified Solution Architect, AWS Certified Data Engineer

Experience

Here are some of the highlights from my recent internships.

  • VEA Full-Stack Engineer
  • Baynovation Software Engineer Intern
  • Tencent Machine Learning Engineer Intern
  • XiuNeng Capital Quant Research Intern

VEA, Full-Stack Engineer (React.js, Node.js, AWS, LangChain, Stripe API) - Sep 2024 – Present
- Fixed 10-15 weekly bugs related to UI, API failures, concurrency, and caching inconsistencies.
- Developed a dynamic SOAP note sidebar for real-time synchronization and enhanced performance.
- Integrated OpenAI and AWS Bedrock APIs for embedding storage, vector search, and Retrieval-Augmented Generation (RAG), improving diagnostic record processing.

Baynovation, Software Engineer Intern (Flask, FastAPI, AWS SageMaker, Huggingface) - May 2024 – Aug 2024
- Built an ETL pipeline (S3 → AWS Glue → Parquet) and integrated SageMaker for feature engineering and model inference.
- Fine-tuned a LLaMA3-based chatbot with LoRA for domain-specific adaptation, improving accuracy and response relevance.
- Deployed the chatbot via API for enterprise-wide usage, iterating system prompts based on analytics feedback.

Tencent, Machine Learning Engineer Intern (PyTorch, TensorFlow, Gymnasium) - Aug 2022 – Oct 2022
- Built a reinforcement learning framework with OpenAI Gym and implemented DQN, achieving 86% task completion accuracy.
- Developed a Transformer-based recommendation system inspired by BERT4Rec, optimizing CTR by 7% in offline evaluations.
- Optimized model training pipelines using CUDA acceleration, reducing training time by 13%.

XiuNeng Capital, Quant Intern (Python, Pandas, Backtrader) - May 2021 – Aug 2021
- Designed and implemented an Event Study Algorithm, improving event impact prediction accuracy by 18%.
- Developed a low-latency event-driven trading system integrating real-time event streaming from broker APIs.
- Leveraged XGBoost for event classification, enabling high-frequency trading decision-making.

Projects

Exploring new possibilities and pushing the boundaries of technology.

Smart Inventory Management System

Full-stack inventory management system using Next.js, Material UI, and Firebase, with OpenAI Vision and HuggingFace's Llama3.1 integration.

View Project

Document Chatbot

Full-stack document chatbot using Express.js and React, with RAG implementation using AWS Bedrock API and Pinecone for vector storage and retrieval.

TikTok Shop Content Recommendation Engine

Content recommendation engine for TikTok Shop using Golang, Python, and TypeScript, with Kafka for real-time data streaming and MySQL for storage.

Book Review Website

Full-stack book review application using React, TypeScript, Java, Spring Boot, and SQL, with user authentication and admin tools.

FashionMNIST Classification with ResNet and VGG

Used ResNet and VGG architectures to classify FashionMNIST dataset, achieving an accuracy of 94%.

Transformer-Based Simple Chatbot

Developed a simple chatbot based on the Transformer architecture. It demonstrates basic conversation abilities.

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