A pretrain-transfer framework for graph optimization. GOFM internalizes network topology through structure-aware random walks and Transformer-based masked reconstruction.

• Self-supervised pretraining on graph structure via structure-aware random walks
• Supports SP, TSP, CVRP, Community Detection & Influence Maximization
• Amazon Last Mile case study — 24.5% distance reduction
• Near-perfect feasibility on city-scale sparse networks

Building a game-theoretic multi-agent framework to study cooperation among LLM-based agents:

• Sequential Public Goods Game with belief updating and conditional cooperation
• Subgame Perfect Nash Equilibrium analysis under full vs. partial observability
• Mechanism design for incentive alignment

Optimizing UAV paths for agricultural data collection:

• DARP & MST algorithms
• Data transmission optimization
• Automated decision-making

Building a multimodal LLM pipeline to convert images (forms, handwriting) into structured text:

• Prompt engineering and fine-tuning for Pix2Text / Pix2Struct
• Mini Program interface; backend in progress
• Focus on accuracy in unstructured data

Analyzing Smart City Pilot Plan impact:

• Multi-period DID model
• 296 cities study
• 20-year data analysis

Full-stack music streaming platform:

• Spring Boot backend
• Vue.js frontend
• MySQL optimization

Hospital transfusion simulation:

• Simio modeling
• Kenyan hospitals study
• UPMC collaboration