Fellows
Junting is a PhD candidate from Shanghai, China. She completed her Master's degree in Computational Science and Engineering at Technical University of Munich in Germany, graduating in September 2024. Prior to that, she obtained her double Bachelor's degrees in Mechatronics from Tongji University in Shanghai, China and from Hochschule München University of Applied Sciences in Germany in 2021. For her master's thesis, she focused on the development of both data-driven methods and Bayesian methods applied on the reconstruction of a complex acoustic field, with broadband forcing and frequency-dependent boundary conditions.
Junting will work towards the development of a general framework for the model reduction of multi-physics acoustic problem. She will try to implement MOR techniques combined with High-Performance Computing (HPC) to reduce the computation.
Sotirios is a current PhD candidate from Patras, Greece. He completed his Diploma (Integrated Master) degree in Mechanical Engineering at the University of Patras, Greece, graduating in August 2023. For his student and diploma thesis, he focused on the development of computationally effective empirical formulas for the prediction of the diffraction field around rigid, absorbing, single or multiple wedges.
Sotiris will work towards developing deep learning methods for a digital twin trained with both physics-based models and measurements. He will try to integrate reduced-order vibro-acoustic models and physics-informed neural networks to accelerate training while incorporating measurement data to improve model accuracy.
Daniel is a PhD candidate at TUM’s Chair of Vibro-Acoustics of Vehicles and Machines. He is from Aracaju, Brazil. He has a Bachelor’s degree in Civil Engineering from the Federal University of Sergipe in Brazil and a Master’s degree in Structural engineering from the University of São Paulo, also in Brazil. For his Master’s thesis, he worked on the numerical stability of the Generalized Finite Element Method, with applications to Fracture Mechanics. The focus of the research was developing novel techniques for improving the method’s underlying system conditioning while keeping the error convergence at optimal rates. A well-conditioned system allows for the proper use of faster solving algorithms, reducing the computational effort.
Daniel will work with acoustic metamaterial numerical simulations, including the effects of viscous and thermal losses. In this context, the main goal of the research is examining the use of Model Order Reduction to cut down on the associated computational costs, making for faster simulations while keeping the solution accuracy as close as possible to that of the Full Order Model.
Mathias is a PhD fellow from Itajaí, Brazil. He worked as a Vibro-Acoustic Engineer for VA One, implementing a FE-informed SEA code based on periodic structures theory. He completed his master’s degree in Vibration and Acoustics at UFSC in 2021, with research focused on FE-informed SEA theory based on non-periodic structures. Prior to that, he obtained his bachelor’s degree in Mechanical Engineering at UFSC in 2019, with research in partnership with Embraer for developing a methodology to predict the damping loss factor of fuselage panels with viscoelastic materials applied.
Mathias will investigate parametric model order reduction methods with large parameter spaces. He will evaluate the accuracy and efficiency of the pMOR methods when applied in the context of design optimization and uncertainty quantification of vibro-acoustic systems.
Rushikesh is currently a Ph.D. student based in Hyderabad, India. He earned his master's degree in machine design from the Indian Institute of Technology Madras in 2024. Before that, he completed his bachelor's degree in mechanical engineering at Malla Reddy Engineering College in Hyderabad in 2019. For his master’s thesis, he worked on the computation of sound power from both baffled and unbaffled plates using independent radiation modes. Additionally, he utilized component mode synthesis to analyze these radiation modes.
Rushikesh will work on the Micro-Macro Homogenization of the mechanical parameters of the porous material. He will also employ the two-level model order reduction schemes to study the porous media.
DC6 - (LAUM/TUM)
TBD
DC7 - Katharina Marburg (KTH/LAUM)
Katharina studied Mechanical Engineering at Technische Universität Dresden in Germany, where she graduated as Diplom-Ingenieurin. Her thesis focused on data-driven methods for condition monitoring of a light rail infrastructure, utilizing acceleration measurements from an on-board sensor system.
In her PhD, Katharina works on model order reduction for Kelvin cell-based metamaterials with the goal of accurately capturing the material response while minimizing computational cost. To achieve this, she will decompose the domain into numerical building blocks to be parameterized and combined at the pre-resolution level, thereby avoiding extensive parameter sweeps.
Pierre is a current PhD student from Nîmes, France. He completed his double Master’s degree in Besançon, France, in Multiphysics Modelling and Mechanic Engineering School. His PhD subject is in the logical following f his Master thesis: Improving exterior acoustics modelling problems by accuracy (New boundary conditions) and efficiency (Model Order Reduction).
Pierre is working on the development of a new implementation of boundary condition in OpenSource Software FEniCSx. This boundary condition is an Absorbing Boundary Condition applicable to general geometries and suitable for Moment Matching technics.
Lucas is a Ph.D. researcher at DTU and KU Leuven from Brazil. He worked at Embraer as a Product Development Engineer, focusing on noise and vibration technology for aircraft cabins. He holds an MSc in Mechanical Engineering, with research centered on topology optimization of aircraft fuselages for low vibration. He earned his Bachelor's degree in Mechanical Engineering (Bac+5) from UFSC in 2022, contributing to projects with Embraer and Petrobras as a research assistant at LVA. His expertise includes vibroacoustic modeling, structural optimization, and computational methods.
Lucas will work in broadband vibroacoustic shape optimization of electroacoustic devices using model order reduction methods. He will try to combine MOR techniques combined with adjoint gradient optimization method to improve sound quality of loudspeakers.
Ravi is a current PhD candidate from Visakhapatnam, India. He completed his Master's degree in Mechanical Engineering at Indian Institute of Technology Bombay (IITB) in India, graduating in August 2022. Prior to that, he obtained his Bachelor's degree in Mechanical Engineering from Indian Institute of Technology Kanpur (IITK) in India. During his master's thesis, he developed control amenable dynamic models for ultra-flexible robots. Post masters, he worked as a senior engineer at ZF India where he focussed on Reinforcement algorithms for self-driving vehicles and MPC for optimal thermal control of e-trailers.
Ravi will work towards the development of a general framework for the Multi-fidelity reduced order modelling of structural acoustics. The goal is to propose innovative approaches for inverse identification of acoustic material properties using MOR techniques combined with Machine Learning methods.