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Structural Sensing and Mechanics Group

Lead by Prof. Shenghan ZHANG

Structural Engineering

Structural Health Monitoring

Structural Analysis

Data Science

Current Member

Sudao HE
(何苏道)

Post-doctral Fellow

  • Ph D – Control Theory and Control Engineering, NUAA
  • B.E – Nanjing University of Aeronautics and Astronautics (NUAA)

Sudao’s research interests include digital twin with incomplete and unreliable data, and its application in fault diagnosis and structural health monitoring. 

Research Area:

  • Digital Twin
  • Structural Health Monitoring
  • Fault Diagnosis
  • Machine Learning, especially zero-shot learning, incremental learning and generative learning

Hobbies: Basketball, Fitness, Badminton.

Gang ZHAO
(赵刚)

Post-doctral Fellow

  • Ph D – Dalian University of Technology
  • B. E and M. E – Wuhan University of Technology

Research Area:

  • Constitutive relationship of interface
  • Defect detection
  • Multi-scale modeling, mechanical characterization and structural optimization
  • Joining technology of carbon fiber-reinforced composite

Hobbies: Swimming

Hanqing ZHANG
(张寒青)

Post-doctral Fellow

  • Ph D – Civil Engineering, Tongji University
  • B. E – Department of Civil Engineering, Tongji University

Hanqing is currently a post-doctoral fellow in the Structural Sensing and Mechanics Group at the HKUST. She has received her Diploma in Civil Engineering from Tongji University in China (2017). In 2023, she successfully defended the Ph.D. thesis entitled “Data-driven seismic damage evaluation method for shear wall structures”. The main idea of the thesis was to propose a novelty seismic damage evaluation method leveraging Structural Health Monitoring (SHM) data for rapid and accurate post-earthquake safety assessment and decision. From 2021 to 2023, she experienced a two-year visit study to the Chair of Structural Mechanics and Monitoring at ETH Zürich.

Since February 2024, she joined the HKUST to continue her research. Her current research interest lies in the condition assessment of structures adopting SHM data and the post-earthquake performance evaluation for infrastructures. Hopefully, she can contribute to unlocking the potential of seismic damage evaluation by fusing different sensor data and corresponding post-earthquake decision-making frameworks.

Research Area:

  • Structural Health Monitoring
  • Intelligent Seismic Damage Assessment of Engineered Systems
  • Post-earthquake Structural Performance Evaluation
  • Structural Vibration Control

Hobbies: Cooking, Hiking, Snowboarding.

Cong CHEN
(陈聪)

Research Assistant

  • M. E – Civil Engineering, Lanzhou University
  • B.E – Lanzhou Univeristy

Research Area:

  • Structural Analysis
  • Optical Fiber Sensors

Hobbies: Table tennis, Reading.

Jun CHEN
(陈军)

Ph D. Student

  • M. E – Architecture & Civil Engineering, Southeast University
  • B.E – Beijing University of Technology

Research Area:

  • Structure Mechanism
  • Earthquake
  • MiC
  • Finite Element Method
  • Constitutive Model

Hobbies: Badminton, Hiking.

Xuanyi LU
(鲁选一)

Ph D. Student

  • M. E – Bridge and Tunnel Engineering, SWJTU
  • B.E – Southwest Jiaotong University (SWJTU)

Research Area:

  • Structural Engineering
  • Optical Fiber Sensors

Hobbies: Basketball, Thriller movies, Pop music.

Zetao Wang
(王泽涛)

Ph D. Student

  • M. E – Architectural and Civil Engineering, Tongji University
  • B.E – Tongji University

Research Area:

  • Structural Dynamics
  • Structural Analysis
  • Machine Learning

Hobbies: Reading, Movies, Video Games.

Hanpeng Wang
(王汉鹏)

Ph D. Student

  • M. E – Disaster Mitigation for Structures, Tongji University
  • B.E – Civil Engineering, Southeast University

Research Area:

  • Structure Health Monitoring
  • Advanced Sensing Technology

Hobbies: Hiking, Films, Bouldering.

Former Member

Daniz TEYMOURI

Former member (2023-2024 Post-doctral Fellow )

  • Ph D – Civil Engineering, Hong Kong University of Science and Technology
  • B. E and M. E – Iran University of Science and Technology

Daniz is a former post-doctoral fellow in the Structural Sensing and Mechanics Group at the Hong Kong University of Science and Technology. Her specialization is in Data-driven Methodologies for Inverse Problems in Structural Health Monitoring. Her research interests include Virtual Sensing Techniques for Response Reconstruction and System Identification, Uncertainty Quantification in Inverse SHM Problems, and Physics Informed Machine Learning.

In the Structural Sensing and Mechanics group, Daniz focuses on conducting high-caliber research to address Structural Dynamics problems. She strongly believes in teamwork and collaborative research and highly values mentorship and continuous learning. Daniz actively participates in teaching and extracurricular activities and is always available to answer questions.

Research Area:

  • Uncertainty Quantification
  • Bayesian Inference
  • Virtual Sensing
  • Finite Element Model Updating
  • Probabilistic Machine Learning