Meet the DVU group team members!

The  Data, Vibration and Uncertainty (DVU) Group is the research team of Dr Alice Cicirello and currently includes members at the University of Cambridge, TU Delft and University of Florence.  

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• Research Associates and Assistants

  • Mr Christos Lathourakis, (2022-2023) , MVU lab,  Mechanics and Physics of Structure Section, Department of Engineering Structures, TU Delft.
    Project title: Physics-Enhanced Machine Learning for friction identification

  • Luca Marino (2022-2023) , MVU lab,  Mechanics and Physics of Structure Section, Department of Engineering Structures, TU Delft.
    Project title:  Monitoring of localised nonlinearities 

  • Filippo Giunta (2020-2021), MVU lab,  Mechanics and Physics of Structure Section, Department of Engineering Structures, TU Delft.
    Project title:  Machine Learning Techniques for efficient Uncertainty Quantification

• Visiting Research Associates

  • Oindrila Kanjilal (2023) , MVU lab,  Mechanics and Physics of Structure Section, Department of Engineering Structures, TU Delft (From TU Munich).
    Project title: Structural Design Optimization by Variational Bayesian Monte Carlo Method    -  funded through the BayFOR programme.

• PhD students

  • Felipe Igea (2019-2024), DVU lab, Engineering Science Department, University of Oxford.
    09-12/22 visiting PhD student at MIT, AeroAstro - ACDL group
    05-07/23 visiting PhD student at TU Delft.
    Project title (ICASE PhD studentship funded by SLB):  Probabilistic Uncertainty Quantification for Structural Dynamics Under Limited Data

  • Adolphus Lye (2018-2022), Affiliated member of the DVU group,  Institute for Risk and Uncertainty at the University of Liverpool - co-supervised with Prof. Edoardo Patelli.
    Project title: Robust and Efficient Probabilistic Approaches towards Parameter Identification and Model Updating

  • Luca Marino (2018-2022), DVU lab, Engineering Science Department, University of Oxford - co-supervised with  Prof.  David Hills.
    Project title (ICASE PhD studentship funded by Rolls-Royce):  Dynamic analysis of mechanical systems with Coulomb friction

• Visiting PhD students

  • Thomas Potthast  (2024), DVU group, Engineering Department, University of Cambridge (from Leibniz University Hannover (LUH)
    Project title:  Model updating for structural health monitoring using sliced distributions. 

  • Luigi Sibille  (2024), DVU group, Engineering Department, University of Cambridge (from NTNU)
    Project title: Virtual sensing and impact force estimation on an operating ferry quay via Gaussian process latent force model

  • Filippo Giunta (2017-2018), DVU lab, Engineering Science Department, University of Oxford (from University of Messina).
    Project title:  Analysis of jointed beams with step changes in material and cross-section under static and dynamic loading (paper)

• Master Students 

  • Matthew Hendricks (2024-25), DVU group, Engineering Department, University of Cambridge. Meng thesis.
    Project: From Text To Computational Models For Dynamical Systems

  • Jamie Lai (2024-25), DVU group, Engineering Department, University of Cambridge. Meng thesis.
    Project: Strategies to extend the PhI-SINDy framework to identify governing equations and latent forces for dynamical systems with vibro-impact nonlinearities

  • Thomas Masding (2024-25), DVU group, Engineering Department, University of Cambridge. Meng thesis.
    Project: Machine Learning for Equation Discovery of Spider Dynamics

  • Saurabh Mahajan, (2022-2023), MVU lab,  Structural Mechanics MSc student, TU Delft.
    Project: Machine learning techniques for investigating the Coulomb friction and hysteresis in structural joints

  • Christos Poirazis (2021-2023), MVU lab,  Offshore & Dredging MSc student, TU Delft. In collaboration with RWS
    Project: Instrumentation of an Offshore Nautical Radar and platform with a sensor suite for measure vibrations in situ 

  • Christos Lathourakis (2021-2022), MVU lab,  Structural Mechanics MSc student, TU Delft. Co-supervision with Dr. Andriotis.
    Project: An integrated framework of deep reinforcement learning and Bayesian inference for the optimal maintenance planning of structural systems

  • Vasileios Sfetsios (2021-2022), MVU lab,  Offshore & Dredging MSc student, TU Delft. In collaboration with RWS
    Project: Development of a Dynamic Model of an Offshore Nautical Radar and platform  for Fatigue Damage Analysis

  • Menelaos Papamichelakis (2020-2021), MVU lab,  Structural Mechanics MSc student, TU Delft.
    Project: Damage identification techniques on complex beam bridges under moving vehicle loads

  • Mikhail James (2020-2021), MVU lab,  Structural Mechanics MSc student, TU Delft.
    Project: Buckling analysis of jointed structural elements

  • Jan Koune (2020-2021), MVU lab,  Offshore & Dredging MSc student, TU Delft. In collaboration with TNO
    Project: Bayesian system identification for structures considering spatial and temporal dependencies

  • Bart Jacobse (2020-2021), MVU lab,  Offshore & Dredging MSc student, TU Delft. In collaboration with Damen
    Project: Non-Linear block load corrections for dry docking

  • Luuk Fassen (2020-2021) - co-supervised at TU Delft, in collaboration with Fugro.
    Project: FBG optical fibers in proof loading of concrete slab bridges

  • Rens Van Lierop (2020-2021) - co-supervised at TU Delft, in collaboration with IMd.
    Project: The opportunities of supplementary damping systems in Dutch high-rise buildings

  • Andreea-Maria Oncescu (2018-2019), DVU lab, Engineering Science Department, University of Oxford. MEng thesis (4YP report).
    Project: Failure detection of low-cost wearable devices using recorded data and reports (paper 1, paper 2)

  • Jonathan Collins (2018-2019), DVU lab, Engineering Science Department, University of Oxford. MEng thesis (4YP report).
    Project: Derivation of seismic fragility curves for Nepalese houses

  • Philemon Kwok (2018-2019),  DVU lab, Engineering Science Department, University of Oxford. MEng thesis (4YP report).
    Project: An approach for detecting failures in real time monitoring systems for automotive applications

  • Christopher Sayers (2018-2019), DVU lab, Engineering Science Department, University of Oxford. MEng thesis (4YP report).
    Project: Improving performance of radio control cars using modelling and testing

  • Atit Kudal (2017-2018), DVU lab, Engineering Science Department, University of Oxford. MEng thesis (4YP report).
    Project: Non-metallic dynamic material property testing (paper)

  • Felipe Igea (2017-2018), DVU lab, Engineering Science Department, University of Oxford.  MEng thesis (4YP report).
    Project: Measurement of elastic properties of panels by vibration (paper)

• Visiting MSc research students 

  • Theo Barottin (2022),  ERASMUS+ and Bourse De Stage A L'international from the Univerisite Paris-Saclay, - MVU Lab, TU Delft.
    Project: Uncertainty propagation in large scale numerical models

  • Joanna Zou (2021), Fulbright Scholar, TU Delft. Co-supervised with Dr. Lourens (main Supervisor). In collaboration with Siemens-Gamesa
    Project: Gaussian process latent force models for virtual sensing in a monopile-based offshore wind turbine (paper1, paper2)

  • Bruno Di Dato (2017-2018), DVU lab, Engineering Science Department, University of Oxford.
    Project title: Vibration performance assessment of a plate with damaged constrained layer damping patches (paper)

• Research Interns 

  • Shaohong Zhong (2019), DVU lab,  Engineering Science Department, University of Oxford - EUROP project  in collaboration with MIT
    Project: Enhanced System Engineering using Machine Learning and Natural Language Processing (paper)

  • Daniel Riddoch (2019), DVU lab, Engineering Science Department, University of Oxford- Rolls-Royce
    Project: Numerical analysis of a single degree of freedom with coulomb damping (paper)

  • Felipe Igea (2018), DVU lab, Engineering Science Department, University of Oxford- Rokos internship.
    Project:  Manufacturing variability assessment combining vibro-acoustic testing and physics-based models (paper)