Alexander Rodríguez

My work advances AI methods for modeling complex spatiotemporal dynamics to support trustworthy data-driven decision-making. Our research addresses problems at the intersection of machine learning, time series analysis, scientific modeling (AI for science), uncertainty quantification, and multi-agent systems, with primary applications in public and environmental health and community resilience.

See my publications here.

Recent updates:

• At AAMAS 2025, I will be giving an invited keynote talk at the workshop on Autonomous Agents for Social Good (AASG).
• I was selected to attend and present our research at the US National Academies Symposium Connections to Sustain Science in Latin America.
• At AAAI 2025, I gave an invited talk at the Bridge on Knowledge-guided Machine Learning and facilitated a tutorial on Data-driven Decision-making in Public Health.
• Our paper “Neural Conformal Control for Time Series Forecasting” led by Ruipu Li was accepted to AAAI 2025 (main technical track).
• I gave a talk at the MIT Institute for Data, Systems, and Society (IDSS) on Deep Learning Methods for Public Health Prediction.
• I am co-organizing AAMAS 2025 serving as co-chair for sponsorship.