University of Florida
At the University of Florida, I am a research assistant working on AI-agent frameworks for ridesourcing forecasting and prescriptive analysis.
- Developing an AI-agent layer that integrates with spatio-temporal deep learning models (e.g., GCNs, CNN-RNN/Transformer hybrids) to enable real-time forecasting and prescriptive analytics for ride-sourcing demand.
- Designing automated mechanisms for "what-if" policy analysis, allowing simulation of interventions such as dynamic congestion pricing or infrastructure changes.
- Implementing agent-based optimization to iteratively search for interventions that optimize stakeholder objectives (e.g., minimizing passenger wait times, balancing vehicle distribution).
- Investigating scalable deployment strategies for AI agents across heterogeneous urban zones, comparing global versus local agent paradigms for improved forecasting and policy relevance.