Truong-Vinh HoangTechnische Universitat Braunschweig www.tu-braunschweig.de/wire/Institute of Scientific Computing truong-vinh.hoang@tu-bs.deMuhlenpfordtstrasse 23, hoang.tr.vinh@gmail.com38106 Braunschweig, Germany +49-531-391-3008

Education and qualification

• Sept. 2017, PhD. in applied sciences, Department of Aerosapce and mechanical Engi-neering, Faculty of Applied Sciences, University of Liege, Belgium.

- Thesis: Stochastic multi-scale modelling of adhesion contact failure in MEMS.• Jun. 2013, Master in mechanical engineering, University of Liege, Belgium.• Jun. 2010, B.Eng in mechatronics, Bach Khoa University, Ho Chi Minh city, Vietnam.

Research experience

• Since Oct. 2017: Postdoctoral researcher at the Institute of Scientific Computing,Faculty of Information, Carl-Friedrich-Gauß-Fakultat, Technische Universitat Braunschweig,Germany.

- Probabilistic inference, data assimilation, Ensemble Kalman filter,- Deep learning in uncertainty quantification,- Parameter identification on random set models.

• Sept. 2013 - Sept. 2017: Phd candidate at the University of Liege, Belgium.- Stochastic multi-scale finite element method (FEM),- Contact behaviour between non-Gaussian random surfaces,- Micromechanics.

• Aug. 2010 - Aug. 2011: Teaching assistant at Bach Khoa University, Vietnam.

Teaching experience

List of master-level courses that I have assisted and gave lectures:•“Uncertainty Quantification, Parametric Problems, and Model Reduction”(2019 link)•“Seminar: Deep Learning and Mathematics behinds it” (2018, 2019 link)•“Practical Course in Simulation of Fluid Dynamics” (2017, 2018 link)•“Elements of Stochastic processes” (2013 link)

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Skills

• Programming languages: Python, C++, Matlab• Packages for scientific computing: Numpy, Scipy, Matplotlib• Machine learning tools: Tensorflow, Keras• Finite element method (FEM) softwares: Fenics, FreeFEM++• Productivity tools: Latex, Jupyter notebook-lab• Other: High performance computing, Linux OS, Bash script

Awards

• FRIA fellowship (Belgian national fund for researches in industry and agriculture -F.R.S.-FNRS) for PhD research, 2013 - 2017.• Full scholarship for Master program at University of Liege, Belgium 2011-2013.• Award for top-scorer in the university national intake examination, Vietnam, 2005.

Languages

• English fluent• German intermediate• French upper intermediate• Vietnamese mother tongue

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List of publications

Journal publications

[1] Drieschner, M, Matthies, HG, Hoang, T. V., et al. (2019) Analysis of polymorphicdata uncertainties in engineering applications. GAMM-Mitteilungen.

[2] Hoang, T. V., & Matthies, H. G. (2018). Non-deterministic inference usingrandom set models: theory, approximation, and sampling method. arXiv preprintarXiv:1811.10446.

[3] Hoang, T. V., Wu, L., Golinval, J. C., Arnst, M., & Noels, L. (2018). Stochasticmultiscale model of MEMS stiction accounting for high-order statistical momentsof non-Gaussian contacting surfaces. Journal of Microelectromechanical Systems, (2),137-155.

[4] Hoang, T. V., Wu, L., Paquay, S., Golinval, J. C., Arnst, M., & Noels, L. (2017). Acomputational stochastic multiscale methodology for MEMS structures involvingadhesive contact. Tribology International, 110, 401-425.

[5] Hoang, T. V., Wu, L., Paquay, S., Obreja, A. C., Voicu, R. C., Muller, R., & Noels,L. (2015). A probabilistic model for predicting the uncertainties of the humidstiction phenomenon on hard materials. Journal of Computational and Applied Math-ematics, 289, 173-195.

Proceeding of international conferences

[6] Hoang, T.V., Rosic, B. and Matthies, H.G., 2018. Characterization and propaga-tion of uncertainties associated with limited data using a hierarchical parametricprobability box. PAMM, 18(1), p.e201800475.

[7] Hoang, T. V., Wu, L., Paquay, S., Golinval, J. C., Arnst, M., & Noels, L. (2016,April). A study of dry stiction phenomenon in MEMS using a computationalstochastic multi-scale methodology. In Thermal, Mechanical and Multi-Physics Simu-lation and Experiments in Microelectronics and Microsystems (EuroSimE), 2016 17th Inter-national Conference on (pp. 1-4). IEEE.

[8] Rosic, B., Kumar Shivanand, S., Hoang, T. V., & G. Matthies, H. (2018). Iterativespectral identification of bone macroscopic properties described by a probabilitybox. PAMM, 18(1), e201800404.

[9] Hoang, T.V., Wu, L., Paquay, S., Golinval, J.C., Arnst, M. and Noels, L., 2017. Astochastic multi-scale model for predicting MEMS stiction failure. In Micro andNanomechanics, Volume 5 (pp. 1-8). Springer, Cham.

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