MIT Senseable City Lab

I presented this talk to MIT Senseable City Lab and its global City Science research network, sharing recent work on using geospatial AI to support scalable environmental monitoring under limited data and testing budgets. The talk introduced FOCUS, a noise-aware geospatial deep learning framework for predicting PFAS contamination in surface water by integrating land cover, hydrological flow, and source proximity. I highlighted results demonstrating improved robustness over traditional methods and discussed future directions in active geospatial search and adaptive sampling to guide real-world environmental decision-making.

Jun 18, 2025 1:00 PM

Invited Talk at MIT Senseable City Lab