63 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- ETH ZurichCH8 papers
- National University of SingaporeSG6 papers
- Arts et MétiersFR2 papers
- Hong Kong University of Science and TechnologyHK2 papers
- Nanyang Technological UniversitySG2 papers
- Singapore-ETH CentreSG2 papers
- GeoInformation (United Kingdom)GB1 paper
- Heriot-Watt UniversityGB1 paper
- Institute of Catastrophe Risk ManagementSG1 paper
- Sun Yat-sen UniversityCN1 paper
- Teikoku Pharma (United States)US1 paper
- The Hong Kong University of Science and Technology (Guangzhou)CN1 paper
12 papers
MatchLM2Lite: A Scalable MLLM-to-Lite Framework for Reproduced Content Identification
Xiaotian Fan, Hiok Hian Ong, David Yuchen Wang +3
Content moderation is critical for online video platforms to ensure content safety, protect creators, and sustain positive user experiences. Beyond filtering harmful content, platf…
Bidirectional yet asymmetric causality between urban systems and traffic dynamics in 30 cities worldwide
Yatao Zhang, Ye Hong, Song Gao +1
Understanding how urban systems and traffic dynamics co-evolve is crucial for advancing sustainable and resilient cities. However, their bidirectional causal relationships remain u…
Quantifying the Value of Seismic Structural Health Monitoring for post-earthquake recovery of electric power system in terms of resilience enhancement
Huangbin Liang, Beatriz Moya, Francisco Chinesta +1
Post-earthquake recovery of electric power networks (EPNs) is critical to community resilience. Traditional recovery processes often rely on prolonged and imprecise manual inspecti…
A Multi-Model Probabilistic Framework for Seismic Risk Assessment and Retrofit Planning of Electric Power Networks
Huangbin Liang, Beatriz Moya, Francisco Chinesta +1
Electric power networks are critical lifelines, and their disruption during earthquakes can lead to severe cascading failures and significantly hinder post-disaster recovery. Enhan…
Modal Decomposition and Identification for a Population of Structures Using Physics-Informed Graph Neural Networks and Transformers
Xudong Jian, Kiran Bacsa, Gregory Duthé +1
Modal identification is crucial for structural health monitoring and structural control, providing critical insights into structural dynamics and performance. This study presents a…
Experimental study of developing free-falling annular flow in a large-scale vertical pipe
Yunpeng Xue, Colin Stewart, David Kelly +2
Annular flow is the primary characteristic of unsteady wastewater flow, which initiates entrained air and sets up the air pressure regime within the system - an important design co…
Impact of street canyon morphology on heat and fluid flow-an experimental water tunnel study using simultaneous PIV-LIF technique
Yunpeng Xue, Yongling Zhao, Shuo-Jun Mei +2
Urban areas are known for their complex atmospheric environments, with the building morphology having a significant impact on local climate patterns, air quality, and overall urban…
Neural Extended Kalman Filters for Learning and Predicting Dynamics of Structural Systems
Wei Liu, Zhilu Lai, Kiran Bacsa +1
Accurate structural response prediction forms a main driver for structural health monitoring and control applications. This often requires the proposed model to adequately capture…
Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structures
Zhilu Lai, Wei Liu, Xudong Jian +3
The order/dimension of models derived on the basis of data is commonly restricted by the number of observations, or in the context of monitored systems, sensing nodes. This is part…
Physics-guided Deep Markov Models for Learning Nonlinear Dynamical Systems with Uncertainty
Wei Liu, Zhilu Lai, Kiran Bacsa +1
In this paper, we propose a probabilistic physics-guided framework, termed Physics-guided Deep Markov Model (PgDMM). The framework targets the inference of the characteristics and…
An efficient surrogate-aided importance sampling framework for reliability analysis
Wang-Sheng Liu, Sai Hung Cheung, Wen-Jun Cao
Surrogates in lieu of expensive-to-evaluate performance functions can accelerate the reliability analysis greatly. This paper proposes a new two-stage framework for surrogate-aided…
Identifying Critical Risks of Cascading Failures in Power Systems
Hehong Zhang, Chao Zhai, Gaoxi Xiao +1
Potential critical risks of cascading failures in power systems can be identified by exposing those critical electrical elements on which certain initial disturbances may cause max…