MS in Applied Data Intelligence @ San Jose State University | Imperial College London Alumna
Bridging the gap between Software Project Management and Technical Execution. I build scalable data pipelines, deep learning models, and full-stack AI applications.
- Languages: Python, Java, C++, SQL, JavaScript (Node.js/React)
- AI & Deep Learning: PyTorch, TensorFlow, CNNs (AlexNet), NLP, Scikit-learn
- Data Engineering: Spark, Hadoop, HDFS, Airflow, dbt, Snowflake, MongoDB
- Agentic AI: LangGraph, Claude MCP (Model Context Protocol), FastAPI
- Full Stack: React, Express, RESTful APIs, Docker
- Refactored sequential scripts into a Stateful Graph Architecture with modular nodes (Planner, Reviewer, Supervisor).
- Implemented fault-tolerant execution and shared memory for complex agentic workflows.
- Tech: Python, LangGraph, OpenAI/Claude API
- Built and trained the AlexNet architecture using PyTorch on ImageNet subsets.
- Optimized performance via custom Kaiming initialization and Cosine Annealing LR scheduling.
- Tech: PyTorch, Computer Vision, GPU Computing
- Designed a scalable MapReduce pipeline at Imperial College London to process neuroscience data.
- Integrated SEEP big data platform with HDFS to enhance throughput.
- Tech: C++, Hadoop, Distributed Systems
- Built a local MCP server to expose external APIs (TheMealDB) to LLMs via JSON endpoints.
- Tech: Python, Node.js, React, MCP Inspector
- LinkedIn: [Jie (Jane) Heng]https://www.linkedin.com/in/jie-heng-411741293/
- Email: janeheng.ic@gmail.com
- Status: H4 EAD (No sponsorship required)