SALGO Startup Collaboration

This project involved an industry-transfer collaboration connected with SALGO, focused on the development of a data-driven system for detecting social agents and modeling population dynamics in event environments.

The work combined machine learning, graph theory, and applied data analysis to study collective behavior and event-level population patterns. The project was connected with competitive innovation programs and industry-collaboration events.

Main components

• CNN-based detection methods.
• Graph-theory modeling of social agents.
• Population-dynamics analysis in event environments.
• Applied data-science workflows.
• Collaboration between academic research and startup-oriented innovation.

Context

The project was selected in competitive innovation environments and connected with industry-facing initiatives, including technology-transfer and entrepreneurship programs.