Te Pei

Te Pei is an Assistant Professor in the Department of Civil Engineering at The City College of New York (CCNY), with affiliations to the CUNY-CREST Institute and Earth System Science and Environmental Engineering programs. His research focuses on geohazards, geotechnical engineering, and machine learning applications in civil infrastructure, particularly in landslide susceptibility mapping, flood quantification, and risk assessment frameworks. He integrates domain knowledge with advanced ML techniques to address challenges in geotechnical analysis and hazard mitigation.

Te Pei's work emphasizes cross-disciplinary approaches, combining physics-informed models with deep learning to improve predictive accuracy across heterogeneous environments. His recent studies include studies on rainfall-induced landslides in Western Pennsylvania and debris flows in Colorado, utilizing meta-learning and domain adaptation techniques. He also explores concrete property prediction and spatiotemporal modeling for infrastructure resilience.

Notable contributions include developing novel frameworks for landslide susceptibility prediction using physics-guided neural networks and cloud-based platforms for landslide database management. His research has practical applications in transportation safety (e.g., cut slope hazard assessment using track inspection videos) and disaster response strategies.