3 papers
physics.geo-ph2026
An Agentic Interface for End-to-End Probabilistic Seismic Hazard and Risk Analysis
Sreenath Vemula, Pierre Jehel, Fabrice Cotton +1
Probabilistic seismic hazard and risk analyses are backbone to building codes, insurance pricing, and disaster management. Yet their open-engine pipelines remain accessible primari…
cs.LG2025
Breaking the Black Box: Inherently Interpretable Physics-Constrained Machine Learning With Weighted Mixed-Effects for Imbalanced Seismic Data
Vemula Sreenath, Filippo Gatti, Pierre Jehel
Ground motion models (GMMs) are critical for seismic risk mitigation and infrastructure design. Machine learning (ML) is increasingly applied to GMM development due to expanding st…
eess.SP2025
Graph Transformer-Based Flood Susceptibility Mapping: Application to the French Riviera and Railway Infrastructure Under Climate Change
Sreenath Vemula, Filippo Gatti, Pierre Jehel
Increasing flood frequency and severity due to climate change threatens infrastructure and demands improved susceptibility mapping techniques. While traditional machine learning (M…