Digital and Resilient Infrastructure

News

Upcoming Events:

Presentations: 

Research 

We tackle the challenge of managing and analyzing the large volumes of data generated by infrastructure systems using advanced tools such as SmartCard, GPR, LiDAR, high-speed cameras, and environmental sensors. The goal is to enhance data collection, storage, and integration techniques from diverse sources, ensuring more efficient demand management, infrastructure investments and supporting timely, informed decision-making.

Research Objectives

To develop multidimensional anomaly detection and pattern recognition algorithms for visble and invisible defects and early warning system.

To establish lightweight sensing algorithms such as computer vision algorithms to interpret image and video data, LiDar data for 3D reconstructing, IMU for dynamic motions, etc.

To develop short-term and long-term predictive maintenance models for dynamic maintenance schedules and risk mitigation plan.


Research Goals and Benefits

Develop intelligent transportation infrastructure monitoring and predictive maintenance algorithms

Enhance rail safety, efficiency, and infrastructure resilience.

Enable data-driven decision-making for cost-effective capital investments.

Promote climate resilience, and reliable multimodality transport in Rail, Road, Air, and more.

Team

Yili (Kelly) Tang, Ph.D., P.Eng

Assistant Professor

Tanjian Wei
Ph.D.
Postdoctoral associate in Western

Suryakant Buchunde
PhD research student 

Duha Abdallah
MESc research student 

Zelin Zhang
MESc research student 

Industrial partners