Muhammad Zohaib Sarwar
About
Introduction:
I am a Postdoctoral Scientist at the Norwegian University of Science and Technology (NTNU), where I conduct cutting-edge research on wheel-wear estimation and prediction for the Norwegian rail network. With a PhD in Engineering from NTNU, I have a strong background in structural dynamics, numerical optimization, and Machine Learning.
My career goal is to solve complex engineering challenges through innovative data-driven solutions, using advanced machine learning and AI techniques. I have successfully applied my skills and knowledge to enhance structural health monitoring and predictive maintenance for various engineering systems, such as trains, buses, and bridges. I have also collaborated with leading industry partners, such as ABB, Stadler, and Norske Tog, to optimize control processes and maintenance actions, and to extract actionable insights from extensive field data. I am always eager to learn new technologies and tools, and to share my findings and insights with others.
The broader area of research interest is in Digitalisation, Automation, Structural dynamic, Rapid condition assessment of infrastructure, using machine learning, big data analysis, Statistical modelling, transfer learning, Time-series analysis, Digital signal processing, WSN technologies and indirect monitoring techniques.
European Eurostars project(2022-2023): ICD - Intelligent Concrete Drying
PhD Project(2019-2022): Automated Structural Condition Assessment for Concrete Bridges
Supervisor: Daniel Cantero
Research
Automated Structural Condition Assessment for Concrete Bridges
The objective of this thesis is to develop a real-time automatic assessment system for existing concrete bridges. This can be achieved by combining the information provided by sensors installed on the bridges and signals sent from passing vehicles
ICD - Intelligent Concrete Drying
The European project Intelligent Concrete Drying (ICD) aims at reducing the CO2 footprint related to the drying process of concrete by 20-30% compared to current levels and at the same time reducing the risk of delays related to the drying process.
Publications
2025
-
Cantero, Daniel;
Sarwar, Muhammad Zohaib;
Malekjafarian, Abdollah;
Corbally, Robert;
Alamdari, Mehrisadat Makki;
Cheema, Prasad.
(2025)
Numerical dataset for benchmarking of drive-by bridge monitoring methods.
Other
-
Cheema, Muhammad Asaad;
Sarwar, Muhammad Zohaib;
Cantero, Daniel;
Rossi, Pierluigi Salvo.
(2025)
Clustered Federated Learning for Population-Based Structural Health Monitoring.
IEEE Internet of Things Journal
Academic article
-
Cheema, Muhammad Asaad;
Sarwar, Muhammad Zohaib;
Lauer, Daniel Cantero;
Rossi, Pierluigi Salvo.
(2025)
Clustered federated learning for population-based structural health monitoring.
IEEE Internet of Things Journal
Academic article
2024
-
Cantero, Daniel;
Sarwar, Muhammad Zohaib;
Malekjafarian, Abdollah;
Corbally, Robert;
Alamdari, Mehrisadat Makki;
Cheema, Prasad.
(2024)
Numerical benchmark for road bridge damage detection from passing vehicles responses applied to four data-driven methods.
Archives of Civil and Mechanical Engineering (ACME)
Academic article
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2024)
Probabilistic autoencoder-based bridge damage assessment using train-induced responses.
Mechanical systems and signal processing
Academic article
-
Cheema, Muhammad Asaad;
Sarwar, Muhammad Zohaib;
Gogineni, Vinay Chakravarthi;
Lauer, Daniel Cantero;
Rossi, Pierluigi Salvo.
(2024)
Computationally Efficient Structural Health Monitoring Using Graph Signal Processing.
IEEE Sensors Journal
Academic article
2023
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel;
Hendriks, Max;
Geiker, Mette Rica.
(2023)
Concrete drying model.
Norges teknisk-naturvitenskapelige universitet
Norges teknisk-naturvitenskapelige universitet
Report
2022
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2022)
Vehicle assisted bridge damage assessment using probabilistic deep learning.
Measurement
Academic article
2021
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2021)
Deep autoencoder architecture for bridge damage assessment using responses from several vehicles.
Engineering structures
Academic article
2020
-
Saleem, Muhammad Rakeh;
Park, Jongwoong;
Lee, Jin-Hwan;
Jung, Hyung-Jo;
Sarwar, Muhammad Zohaib.
(2020)
Instant bridge visual inspection using an unmanned aerial vehicle by image capturing and geo-tagging system and
deep convolutional neural network.
Structural Health Monitoring
Academic article
-
Sarwar, Muhammad Zohaib;
Park, Jongwoong.
(2020)
Bridge Displacement Estimation Using a Co-Located Acceleration and Strain.
Sensors
Academic article
-
Sarwar, Muhammad Zohaib;
Saleem, Muhammad Rakeh;
Park, Jongwoong;
Moon, Do-Soo;
Kim, Dong Joo.
(2020)
Multimetric Event-driven System for Long-Term Wireless Sensor Operation in SHM Application.
IEEE Sensors Journal
Academic article
Journal publications
-
Cheema, Muhammad Asaad;
Sarwar, Muhammad Zohaib;
Cantero, Daniel;
Rossi, Pierluigi Salvo.
(2025)
Clustered Federated Learning for Population-Based Structural Health Monitoring.
IEEE Internet of Things Journal
Academic article
-
Cheema, Muhammad Asaad;
Sarwar, Muhammad Zohaib;
Lauer, Daniel Cantero;
Rossi, Pierluigi Salvo.
(2025)
Clustered federated learning for population-based structural health monitoring.
IEEE Internet of Things Journal
Academic article
-
Cantero, Daniel;
Sarwar, Muhammad Zohaib;
Malekjafarian, Abdollah;
Corbally, Robert;
Alamdari, Mehrisadat Makki;
Cheema, Prasad.
(2024)
Numerical benchmark for road bridge damage detection from passing vehicles responses applied to four data-driven methods.
Archives of Civil and Mechanical Engineering (ACME)
Academic article
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2024)
Probabilistic autoencoder-based bridge damage assessment using train-induced responses.
Mechanical systems and signal processing
Academic article
-
Cheema, Muhammad Asaad;
Sarwar, Muhammad Zohaib;
Gogineni, Vinay Chakravarthi;
Lauer, Daniel Cantero;
Rossi, Pierluigi Salvo.
(2024)
Computationally Efficient Structural Health Monitoring Using Graph Signal Processing.
IEEE Sensors Journal
Academic article
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2022)
Vehicle assisted bridge damage assessment using probabilistic deep learning.
Measurement
Academic article
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2021)
Deep autoencoder architecture for bridge damage assessment using responses from several vehicles.
Engineering structures
Academic article
-
Saleem, Muhammad Rakeh;
Park, Jongwoong;
Lee, Jin-Hwan;
Jung, Hyung-Jo;
Sarwar, Muhammad Zohaib.
(2020)
Instant bridge visual inspection using an unmanned aerial vehicle by image capturing and geo-tagging system and
deep convolutional neural network.
Structural Health Monitoring
Academic article
-
Sarwar, Muhammad Zohaib;
Park, Jongwoong.
(2020)
Bridge Displacement Estimation Using a Co-Located Acceleration and Strain.
Sensors
Academic article
-
Sarwar, Muhammad Zohaib;
Saleem, Muhammad Rakeh;
Park, Jongwoong;
Moon, Do-Soo;
Kim, Dong Joo.
(2020)
Multimetric Event-driven System for Long-Term Wireless Sensor Operation in SHM Application.
IEEE Sensors Journal
Academic article
Part of book/report
-
Cantero, Daniel;
Sarwar, Muhammad Zohaib;
Malekjafarian, Abdollah;
Corbally, Robert;
Alamdari, Mehrisadat Makki;
Cheema, Prasad.
(2025)
Numerical dataset for benchmarking of drive-by bridge monitoring methods.
Other
Report
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel;
Hendriks, Max;
Geiker, Mette Rica.
(2023)
Concrete drying model.
Norges teknisk-naturvitenskapelige universitet
Norges teknisk-naturvitenskapelige universitet
Report
Outreach
2022
-
Academic lectureSarwar, Muhammad Zohaib; Cantero, Daniel. (2022) Data-driven bridge damage detection using multiple passing vehicles responses. IABMAS 2022 - 11th Bridge Safety, Maintenance, Management, Life-Cycle, Resilience and Sustainability , Barcelona 2022-07-11 - 2022-07-14
2021
-
Academic lectureSarwar, Muhammad Zohaib; Cantero, Daniel. (2021) Unsupervised deep learning-based damage detection using the fleet-sourcing concept. SHMII-10 - 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure 2021-06-30 - 2021-07-02