Curriculum vitae

• Developed and optimized Graph Neural Network (GNN)-based AI models for Distribution System State Estimation (DSSE), improving accuracy and scalability.
• Designed and implemented Temporal-Spatial Graph Neural Network (TSGNN)-based models for grid measurement anomaly detection, enhancing grid reliability and predictive capabilities.
• Created advanced Heterogeneous Graph Neural Network (HGNN)-based AI models for time-series power flow analysis.
• Built and enhanced scalable data generation, model training, and inference pipelines using Ray.io and Kubernetes (K8s) to streamline end-to-end workflows and ensure high-performance deployment.

My responsibilities include all items outlined in the Software Developer role at GridOS-DERMS, GE Digital, GE Vernova, as well as:

• Assisting the product manager in defining milestone scopes and refining acceptance criteria for features.
• Breaking down large features into smaller, manageable tasks and providing time estimation to the product manager.
• Collaborating with cross-functional teams, including architects, product managers, and quality assurance engineers to design integration solutions.
• Contributing to the evaluation of new tools and frameworks that have the potential to enhance both application performance and the overall development process.
• Providing mentorship and guidance to junior developers, addressing their questions in the workplace, and actively sharing knowledge with them.

• Design, implement and improve mathematical optimization models to simulate electric power grid with distributed energy resources (DERs) by using GAMS
• Maintain `optimization engine`: the python package to run power flow analysis
• Design, implement and improve OPF(optimal power flow) objectives, e.g : cost minimization, operational envelope, bid fulfillment, etc
• Design, implement and improve RESTful APIs on micro-service to run powerflow analyses. (flask)
• Design, implement and improve Queue-based micro-service to run powerflow analyses. (Kafka)
• Design, implement and improve benchmark testing tools
• Write documentations and white papers for the optimization models and applications developed
• Analysis and validate optimal power flow results of customers' networks, and compare results with published data from IEEE Power & Energy Society (IEEE PES)

• Developing Visualized Supply Chain Management System, include tracking, payment, and invoice generation functions. This web app is built by React (for frontend), MYSQL and Django (for backend).