Our latest preprint led by Yu-Hsuan (Viola) Ho presents ML4EJ: an interpretable machine learning model for decoding the role of urban features in shaping disparities in environmental hazard exposures! arxiv.org/abs/2310.02476

New paper from our lab led by Chiawei Hsu reveals different resilience characteristics in human mobility networks at microscopic vs. Substructure vs macroscopic scales! #NSF_Funded disq.us/t/4jlzzru

The latest paper from our lab led by Chiawei Hsu examined the sensitivity of human mobility network analyses results to the data sources! The findings reveal that human mobility properties obtained from different dataset may not be generalizable due to representativeness issues!

A new preprint led by Bo Li reveal #Resilience curve archetypes & their fundamental properties in power infrastructure using unsupervised #MachineLearning. Findings explain distinct resilience behaviors of triangular vs trapezoidal archetypes. arxiv.org/abs/2310.10030

Excited to share our new paper led by Chia-Fu Liu in which we characterize disaster recovery as a network diffusion process. The findings have EJ implications: the recovery network spillover effects are stronger in disadvantaged communities👇 #NSF_Funded rb.gy/58ov9s

So excited to share our latest preprint led by KaiYin_TAMU in which we present a deep learning-driven community resilience rating model based on intertwined socio-technical systems features. #AI #Resilience #NSF_Funded arxiv.org/abs/2311.01661

New paper from our lab unveils how human mobility networks in 20 U.S. cities affect urban heat exposures, identifying "urban heat traps" where populations frequently move between high-heat areas. Insights like these are crucial for designing healthier, more sustainable cities.

📢 The latest paper from our lab co-led by Akhil Rajput Jacky, Zhewei LIU Chenyue_Liu published in Nature Cities examined population life activity flood exposure to provide a human-centric approach to flood risk analysis. We used millions high-rsolution location based data to

📢The latest preprint from our lab led by Chenyue_Liu presents our #FloodGenome model (interpretable ML model) which reveals universal features that shape property flood risk predisposition in cities! The model also enables classifying property flood risk profile of communitis

We are thrilled to publish this study by Junwei Ma & Ali Mostafavi ✨️, highlighting how coastline and metropolitan counties in the US show large spatial inequality of property flood risk linked to urban density and growth, economy, and racial and income segregation.

📢The latest preprint from our lab led by Yu-Hsuan (Viola) Ho presents our Elev-Vision-SAM model for enhancing automated estimation of the lowest floor elevation of buildings by integrating vision language and foundation models on street view imagery. #AI #ResilienceTech

📢 Recent paper from our lab led by Chenyue_Liu unveils the determinants of health risk disparity in cities using graph machine learning. This AI-based approach provides novel insights for evaluating intertwined features that shape health disparities for inter- and intra-city

📢Recent paper from our lab in collab w Hamed Farahmand Xavier Espinet KaiYin_TAMU presents a new framework for assessing the resilience of road networks, especially in regions with limited data. Our approach considers agency, user, and environmental costs and supports

📢Excited to share our latest preprint led by Natalie Coleman in collab w Chenyue_Liu in which we dissected societal recovery at the finest scale ever examined based on evaluating fluctuations in lifestyle activities of millions of anonimozed users in two major hurricanes! The

📢The latest paper from our lab led by Natalie Coleman in collab w Xiangpeng Li & wonderful Tina Comes presents the research landscape of a decade of research focusing on integrating equity into infrastructure resilience assessment! We unpack various dimension of analysis and

📢New preprint from our lab led by Chia-Fu Liu and Chiawei Hsu reveals the network dynamics of business recovery which unfold via diffusion on pre-disaster visitation network. Key findings: (1) the presence of a diffusion process influencing recovery across the business network;

🚀Excited to share our latest work from UrbanResilience.AI Lab! 🌊FloodDamageCast: A damage nowcasting model that combines  CTGAN for data augmentation with LightGBM, pinpointing high-damage areas often missed by baseline models. authors.elsevier.com/a/1kA937t2zZHE… #MachineLearning #UrbanResilience

Recent paper from our lab led by Chia-Fu Liu presents FloodDamageCast, the first of its kind ML model for near-real-time flood damage nowcasting of structures at fine resolutions (500m x 500m)! The model combines data augmentation (CTGAN) & LightGBM to tackle imbalanced datasets

Humbled and deeply honored to be awarded the 2025 Walter Huber Research Prize by ASCE Headquarters ! Walking in the footsteps of past awardees, many of whom I've long admired and learned from, is truly humbling. asce.org/career-growth/…