AI for Ocean Currents & Tsunami Early-Warning

Grasp core coastal/tsunami physics (shallow-water, bathymetry).

Ingest, QC, align, and grid buoy/HF-radar/altimetry data.

Benchmark baselines vs ML (PINNs, FNOs, encoder–decoders/SSMs).

Apply lightweight data assimilation and read analysis increments.

Produce short-horizon forecasts with calibrated uncertainty.

Detect tsunami-like anomalies and estimate ETA with bands.

Evaluate skill (CRPS, PR/ROC, cost–loss) and set alert thresholds.

Wire an ops pipeline and generate a one-page situation report.

QC, align, and grid buoy/HF-radar/altimetry data (NetCDF/Zarr).

Train baselines + physics-aware ML (PINNs, FNOs, encoder–decoders).

Assimilate observations (EnKF intuition) and visualize increments.

Deliver +6 h surface-current & +24 h buoy forecasts with calibrated uncertainty.

Detect tsunami-like anomalies and estimate ETA with confidence bands.

Evaluate skill (CRPS, PR/ROC, cost–loss) and set tiered alert thresholds.

Ship a minimal ops pipeline (ingest→QC→DA→forecast→UQ→publish) and a one-page situation report.

Coastal & ocean modelers, met-ocean analysts, and early-warning/DRM teams

Data scientists/ML engineers in public agencies, NGOs, or blue-economy startups

Graduate/advanced undergraduate students in Ocean/Climate/EE/CS/ME

Researchers working with buoy, HF-radar, satellite altimetry, or tide-gauge data