Applied ML Systems

A production deep learning pipeline performing multi-location spatio-temporal inundation depth forecasting. Ingests multi-modal meteorological and hydrological time-series, fuses spatial and sequential features, and outputs calibrated depth forecasts across a city-scale sensor network — deployed end-to-end on GCP Vertex AI with TFX orchestration.

TensorFlow · TFX · GCP Vertex AI · Keras · Python

A province-scale geospatial deep learning pipeline predicting fire occurrence and spread probability from fused satellite, meteorological, and topographic features. Outputs geospatial risk maps derived from vegetation indices and spatial embeddings — deployed on GCP Vertex AI with full TFX orchestration.

TensorFlow · TFX · GCP Vertex AI · Keras · Python

A deep learning-based risk assessment system for autonomous drone delivery of hazardous materials in urban environments. Trains on operational data to produce dynamic safety assessments informing route planning, regulatory compliance, and incident prevention.

TensorFlow · Keras · ANNs · Python

A graph-based ML pipeline that models and predicts cascading risk propagation through complex interdependent networks. Uses Genetic Algorithm tuning and NSGA-II multi-objective optimization to identify systemic failure paths — capturing how risks compound across graph-structured systems.

scikit-learn · Graph Algorithms