Muhammad Zohaib Sarwar
Om
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
Forskning
Automated Structural Condition Assessment for Concrete Bridges
ICD - Intelligent Concrete Drying
Publikasjoner
2024
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2024)
Probabilistic autoencoder-based bridge damage assessment using train-induced responses.
Mechanical systems and signal processing
Vitenskapelig artikkel
-
Cheema, Muhammad Asaad;
Sarwar, Muhammad Zohaib;
Gogineni, Vinay Chakravarthi;
Cantero Lauer, Daniel;
Salvo Rossi, Pierluigi.
(2024)
Computationally Efficient Structural Health Monitoring Using Graph Signal Processing.
IEEE Sensors Journal
Vitenskapelig artikkel
-
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)
Vitenskapelig artikkel
2023
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel;
Hendriks, Max;
Geiker, Mette Rica.
(2023)
Concrete drying model.
NTNU, Department of Structural Engineering
Rapport
2022
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2022)
Vehicle assisted bridge damage assessment using probabilistic deep learning.
Measurement
Vitenskapelig artikkel
2021
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2021)
Deep autoencoder architecture for bridge damage assessment using responses from several vehicles
.
Engineering structures
Vitenskapelig artikkel
2020
-
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
Vitenskapelig artikkel
-
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
Vitenskapelig artikkel
-
Sarwar, Muhammad Zohaib;
Park, Jongwoong.
(2020)
Bridge Displacement Estimation Using a Co-Located Acceleration and Strain
.
Sensors
Vitenskapelig artikkel
Tidsskriftspublikasjoner
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2024)
Probabilistic autoencoder-based bridge damage assessment using train-induced responses.
Mechanical systems and signal processing
Vitenskapelig artikkel
-
Cheema, Muhammad Asaad;
Sarwar, Muhammad Zohaib;
Gogineni, Vinay Chakravarthi;
Cantero Lauer, Daniel;
Salvo Rossi, Pierluigi.
(2024)
Computationally Efficient Structural Health Monitoring Using Graph Signal Processing.
IEEE Sensors Journal
Vitenskapelig artikkel
-
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)
Vitenskapelig artikkel
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2022)
Vehicle assisted bridge damage assessment using probabilistic deep learning.
Measurement
Vitenskapelig artikkel
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel.
(2021)
Deep autoencoder architecture for bridge damage assessment using responses from several vehicles
.
Engineering structures
Vitenskapelig artikkel
-
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
Vitenskapelig artikkel
-
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
Vitenskapelig artikkel
-
Sarwar, Muhammad Zohaib;
Park, Jongwoong.
(2020)
Bridge Displacement Estimation Using a Co-Located Acceleration and Strain
.
Sensors
Vitenskapelig artikkel
Rapport
-
Sarwar, Muhammad Zohaib;
Cantero, Daniel;
Hendriks, Max;
Geiker, Mette Rica.
(2023)
Concrete drying model.
NTNU, Department of Structural Engineering
Rapport
Formidling
2022
-
Vitenskapelig foredragSarwar, 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
-
Vitenskapelig foredragSarwar, 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