Data, Vibration and Uncertainty Group

Data, Vibration and Uncertainty Group (2017 - present)

The  Data, Vibration and Uncertainty (DVU) Group (officially started on 18/09/17) is the research team of Dr Alice Cicirello and it has the ambition to tackle fundamental scientific questions and pressing scientific challenges in Engineering for guiding decision making on critical components, structures and systems.  

We believe that advancing only physics-based models, or experiments or data-driven techniques in isolation, would not be enough to tackle these problems. Our research strategy is based on developing and integrating state-of-the-art physics-based models, laboratory experiments, monitoring, data-driven techniques, system identification,  physics-enhanced machine learning, and uncertainty quantification approaches

Most of our research interests focus on the investigation of the dynamic performance of complex engineering systems, critical structures, and important functional components, when subjected to manufacturing variability, uncertainty, nonlinearity and sparse and limited information.  Our aim is to support decision making on such systems at the design-stage and in operating conditions to avoid unexpected failures and/or performance issues. 

Our drive is  to enabling solutions which are applicable in practice in a broad range of scientific fields and industries, including renewable energy, aerospace, automotive, construction and oil & gas. Some specific examples include: engines, wind turbines, bridges, monitoring systems, frictional contacts. Moreover, we enjoy working in cross-disciplinary environments investigating broader applications.

The  Data, Vibration and Uncertainty Group currently includes members at the University of Cambridge,  TU Delft, University of Sheffield, and University of Florence. 

The first DVU group laboratory was the Dynamics, Vibration and Uncertainty (DVU) Lab @ Oxford EngSci (2017-2021). Later small lab experiments were carried out in the Monitoring, Vibration and Uncertainty (MVU) Lab @ TU Delft (2020 - 2023). 

Our research aims to:

To achieve this, we recognize the need to develop techniques:

First version of the friction investigation setup (2018). Picture Credit: L. Marino

on Machine Learning strategies for Marine Cloud Brightening 

Cross-disciplinary research interests: Animal Vibration

One recent example is the collaboration with the Oxford University Zoology Department on the investigation of the vibration generation mechanism in planthoppers, and the ongoing work on spider dynamics in collaboration with the Animal Vibration Lab in the Oxford University Biology Department.

Spider dynamics, Picture taken from https://royalsocietypublishing.org/doi/full/10.1098/rsif.2023.0365

Work with us!

The DVU group is a creative, positive and stimulating research group. We nurture your talent with 1-2-1 weekly or fortnightly meetings, regular fortnightly group meetings, quarterly review group meetings and dedicated technical and soft skills training opportunities. We celebrate diversity, success, and most importantly, we openly chat about setbacks and learn from things that inevitably do not go as planned. We provide flexible working patterns and direct access to a network of international collaborators. We value your time off, your personal space, and your technical contribution. 

The DVU group's core values are: curiosity, innovation, integrity and well-being.

We are always looking for brilliant and motivated new additions to the DVU Group!  

One open position:

Topic: Machine learning strategies for Marine Cloud Brightening

🎓 PhD position in the Centre for Climate Repair and DVU group @ Cambridge within the Aerosol Science CDT

🗓 Deadline for applications: the sooner the better!


Please note:

- The first year training will be done as part of the CDT cohort at the University of Bristol

- year 2-4 of the PhD project (and degree awarding institution) will be the University of Cambridge (Engineering Department)

- More info on the Aerosol Science CDT page


Note: 


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