Research

Selected Publication (full list can be found in Google Scholar)

Li, Xuechun, Paula M. Bürgi, Wei Ma, Hae Young Noh, David Jay Wald, and Susu Xu. "DisasterNet: Causal Bayesian Networks with Normalizing Flows for Cascading Hazards Estimation from Satellite Imagery." In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 4391-4403. 2023.

Hou, James, and Susu Xu. "Near-Real-Time Seismic Human Fatality Information Retrieval from Social Media with Few-Shot Large-Language Models." In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems (SenSys), pp. 1141-1147. 2022.

Susu Xu, Joshua Dimasaka, David J. Wald, and Hae Young Noh. "Seismic multi-hazard and impact estimation via causal inference from satellite imagery." Nature Communications 13, no. 1 (2022): 1-13. (PDF)

Jingxiao Liu, Susu Xu, Mario Berges, Hae Young Noh. “HierMUD: Hierarchical Multi-task Unsupervised Domain Adaptation between Bridges for Drive-by Damage Diagnosis”. Structural Health Monitoring. 2022;0(0). doi:10.1177/14759217221081159. (ASME SHM Best Journal Paper award)

Xiaolin Liu, Rongye Shi, Qianxin Hui, Susu Xu, Shuai Wang, Rui Na, Ying Sun, Wenbo Ding, Dezhi Zheng, and Xinlei Chen. "TCACNet: Temporal and channel attention convolutional network for motor imagery classification of EEG-based BCI." Information Processing & Management 59, no. 5 (2022): 103001.

Susu Xu, and Hae Young Noh. “PhyMDAN: Physics-informed knowledge transfer between buildings for seismic damage diagnosis through adversarial learning". Mechanical Systems and Signal Processing 151 (2021), 107374. (PDF) (ASME SHM Best Journal Paper award, nominated for 2021 Ephrahim Garcia Best Paper Award)

Gang Wang, Shijia Pan, Susu Xu. “Decoupling the Unfairness Propagation Chain in Crowd Sensing and Learning Systems for Spatio-temporal Urban Monitoring”. The 8th ACM International Conference on Systems for Energy-Efficient Built Environments (ACM BuildSys), 2021

Xinlei Chen*, Susu Xu*, Xinyu Liu, Xiangxiang Xu, Hae Young Noh, Lin Zhang, Pei Zhang. “Adaptive Hybrid Model-enabled Sensing System (HMSS) for Fine-Grained Air Pollution Estimation”. IEEE Transactions on Mobile Computing (2020), DOI:10.1109/TMC.2020. 3034270. (* Co-first author) (Link)

Xinlei Chen*, Susu Xu*, Jun Han, Haohao Fu, Xidong Pi, Carlee Joe-Wong, Lin Zhang, and Hae Young Noh, Pei Zhang. “PAS: Prediction-Based Actuation System for City-Scale Ridesharing Vehicular Mobile Crowdsensing.” IEEE Internet of Things Journal, 2020 Jan 21;7(5):3719-34. (* Co-first author) (Link)

Smailagic, Asim, Hae Young Noh, Pedro Costa, Devesh Walawalkar, Kartik Khandelwal, Mostafa Mirshekari, Jonathon Fagert, Adrián Galdrán, and Susu Xu. “O‐MedAL: Online active deep learning for medical image analysis.” Data Mining and Knowledge Discovery 10, no. 4 (2020): e1353. (ICMLA Best paper award)

Susu Xu, Xinlei Chen, Carlee Joe-Wong, Pei Zhang, and Hae Young Noh. “iLOCuS: Incentivizing Vehicle Mobility to Optimize Sensing Distribution in Crowd Sensing.” in IEEE Transactions on Mobile Computing 2019, DOI: 10.1109/TMC.2019.2915838. (Link)

Patents

Susu Xu, Tijmen Blankevoort, Arash Behboodi, Hossein Hosseini. “Deep Neural Network Model Transplantation Using Adversarial Functional Approximation”. US 17/409,725.

Xinlei Chen, Susu Xu, Shijia Pan, Hae Young Noh, Pei Zhang. “Adaptive HMSS: Hybrid Model-enabled Sensing System for Mobile Fine-Grained Air Pollution Estimation”. (Provisional)

Grants

"Rapid, Scalable, and Joint Assessment of Seismic Multi-Hazards and Impacts: From Satellite Images to Causality-Informed Deep Bayesian Networks." National Science Foundation (NSF) CMMI-2242590, Disaster Resilience Research Grant. Lead PI

“Enhancing Wildfire Emergency Management (WEM) Platform with Near Real-Time Sensing Data and Deep Learning.” NIST Measurement Science and Engineering (MSE) Research Grant Programs. Co-PI.

Tier-1 UTC center “Rural Equitable and Accessible Transportation Center (REAT)", and Regional UTC center "Region-2: Center for Social and Economic Mobility for People and Communities through Transportation". USDOT Announcement. SBU Co-PI

“Integrating Satellite Imagery and PAGER Loss Modeling for Improved Building Damage Estimates: Collaborative Research between Stony Brook University and USGS”, USGS Earthquake Hazards Program 2023 (G23AS00249). Sole PI

“Causal Graph-based Joint Estimation of Ground Failure and Building Damage from Satellite Images in Near-Real Time: Collaborative Research with Stony Brook University and USGS”, USGS Earthquake Hazards Program 2022 (G22AP00032). Sole PI

“Reasoning and Mitigating Community Disparity-induced Social-technical Biases for Equitable Road Maintenance”, OVPR seed grants Provostial Seed Grants. Lead PI

“GAANN Fellowship in Civil Engineering for Advancing Smart Infrastructure Systems”, Department of Education. Co-PI