Advances in technology have led to rapid urban development that has manifested in the form of impressive construction over the years. With the simultaneous degradation of aging infrastructure, asset owners are now posed with the predicament of either retrofitting or decommissioning the structure as they deem fit. While visual inspection at times remains the sole identifier of system anomaly, a wider understanding of the remaining serviceable life of the system can be attained using sensor-based real-time measurements.

OSCAR is a multi-disciplinary research group that focuses on real-time structural health monitoring of built infrastructure. To tackle these challenges, the group assimilates data obtained from deployed sensors, into the condition assessment, diagnostics, and virtualization of engineered systems. This is carried out via a fusion of physics-based models, system identification, damage detection, modal analysis, vibration control, time-series analysis, and machine-learning tools. Our applications span a broad range of structural assets; from more conventional infrastructure (bridges, buildings), to burgeoning sectors of wind energy infrastructure, all the way to vehicle and railway infrastructure condition assessment.

Real-time monitoring is evolving fast but requires normative guidelines to be a part of wider safety frameworks in different sectors. With an aim to better understand the infrastructure around us, we are convinced that a proper selection of hardware and algorithmic suite can lead to a smart, intelligent data-driven infrastructure monitoring system where diagnosis, prognosis, and management no longer depend on mere visual readings.

Our group collaborates actively with eminent researchers from international institutions. At present, we collaborate with the University College Dublin, Ireland, University of Nottingham, UK, University Laval, Canada, and Columbia University, USA. We have also developed strong research collaborations with the Indian Institute of Technology Delhi and the Indian Institute of Technology Guwahati.

Interested in joining our group?

Potential Ph.D. candidates with a strong analytical background and an outstanding M.Tech degree in Civil/Mechanical/Aerospace engineering or a related field are encouraged to apply. Prior experience in writing codes in MATLAB/Python/R and finite element modeling software (ANSYS/ABAQUS) is essential for positively contributing to this group. Previous experience in machine learning, signal processing, probability, statistics, condition assessment of wind turbines, and structural health monitoring will be beneficial. Prospective students interested in joining this dynamic group should check the current research focus of the group and directly email me with details of previous research experience, a detailed CV, and a future research plan to be conducted.