Openings (updated 10/2024):
We are actively seeking enthusiastic Ph.D. students to join our dynamic group for the Fall 2025 intake. Selected students will engage in multidisciplinary research spanning one or more of the following areas:
Structural health monitoring and robotic-assisted infrastructure inspection
Adaptive robotics and human-robot collaboration
We invite applications from highly motivated students with a solid foundation in one or more of the following areas: structural health monitoring, robotics, image/signal processing, computer vision, Python programming, machine/deep learning, or related experimental/analytical fields. Candidates with a master’s degree in Civil Engineering or related disciplines are preferred, though exceptional undergraduate students will also be considered. Interested applicants should reach out to Dr. Liang at xliang@tamu.edu with their CV, transcript, TOEFL/IELTS, and GRE scores. Please include details in your email about how your research experiences align with our projects and your future research interests. TAMU’s Ph.D. program in civil engineering is one of the few globally offering an interdisciplinary AI and Data Science track, ideal for candidates aiming to advance AI systems in civil infrastructure and urban systems.
Tazwar Bakhtiyar Zahid, Texas A&M University (08/2025 – present)
Ben Li, Texas A&M University (08/2025 – present)
Zuoxu Wang, Texas A&M University (08/2024 – present)
Yifeng Zhang, Texas A&M University (08/2024 – present)
Jiurun Song (co-chair), Texas A&M University (08/2024 – present)
Yichang Feng (co-chair), Texas A&M University (08/2024 – present)
Chang Liu (co-chair), Texas A&M University (01/2024 – present)
Sibo Tian (co-chair), Texas A&M University (08/2021 – present)
Otokini Cotterell, LSAMP program, Texas A&M University (01/2025 – present)
Kareem A. Eltouny (Ph.D. 2023), University at Buffalo. Dissertation: Machine Learning Approaches for Robust and Practical Structural Health Monitoring
Zhu Chen (Ph.D. 2023, co-chair), University at Buffalo. Dissertation: Learning-Based Control and Trajectory Generation for Drones
Seyed Omid Sajedi (Ph.D. 2022), University at Buffalo. Dissertation: Uncertainty-Assisted Artificial Intelligence for Reliable Structural Health Monitoring
Kareem A. Eltouny (M.S. 2019), University at Buffalo. Thesis: Structural Health Monitoring Using Unsupervised Learning Methods with a View on Post-Earthquake Damage Detection
Zarak Khan Kasi (M.S. 2019), University at Buffalo. Thesis: Frequency-Based Classification of Damage in Structures