Te Pei

Te Pei

from Stony Brook University • 1Post
Geohazards present ongoing threats to lives and infrastructure globally, with their frequency and severity exacerbated by climate change and human activities. Professor Pei’s research focuses on advancing scientific understanding and improving the forecasting of climate-induced geohazards through a combination of physics-based and data-driven modeling. Pei aims to uncover the complex interactions between geohazards, human communities, and infrastructure, contributing to a deeper understanding of urban and regional dynamics, public health, and the resilience of both infrastructure and the environment.
Online Agenda
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Machine Learning for Natural Hazard Prediction

This tutorial provides a step-by-step introduction to building Landslide Susceptibility Models (LSMs) using classical machine learning algorithms. Participants will learn how to preprocess geospatial data, train ensemble models under different data partitioning and cross-validation strategies, interpret feature importance, and evaluate the spatial generalization performance of regional landslide susceptibility predictions.

Te Pei
Written by Te Pei