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IRTG Modern Inverse Problems (MIP)

Kategorie: ‘Student CVs’

Andrea Hanke, M.Sc.

14. November 2018 | von

Contact

Aachen Institute for Advanced Study
in Computational Engineering Science (AICES)
RWTH Aachen
Schinkelstr. 2
52062 Aachen

Office: Room 421b
Phone: +49 241 80 99140
Email: hanke@aices.rwth-aachen.de

Education

01/2019 – Current: Ph.D. Candidate, IRTG at RWTH Aachen University, Germany

10/2016 – 12/2018 Master of Science in Simulation Sciences, RWTH Aachen University, Germany

10/2013 – 09/2016 Bachelor of Science in Material Sciences, RWTH Aachen University, Germany

Theses

  • Understanding the Properties in Resistive Switching Oxides. (Master’s Thesis at the PGI of the Forschungszentrum Jülich)
  • A Computational Study of the Structural and Electronic Properties of Amorphous Antimony (Bachelor’s Thesis at RWTH Aachen University)

Ankit Chakraborty, M.Sc.

14. November 2018 | von

 

Contact

Aachen Institute for Advanced Study
in Computational Engineering Science (AICES)
RWTH Aachen
Schinkelstr. 2
52062 Aachen

Office: Room 424
Phone: +49 241 80 99136
Email: chakraborty@aices.rwth-aachen.de

 

Education

09/2018 – Current: Ph.D. Candidate, IRTG at RWTH Aachen University, Germany

10/2015 – 05/2018: Master of Science in Simulation Science, RWTH, Aachen, Germany

2011 – 2015: Bachelor of Technology in Mechanical Engineering at  Indian Institute of  Technology, Patna, India

 

Research Interests

  Higher Order Galerkin Schemes and Metric based Anisotropic Mesh Optimization. 

 

Theses

  • Numerical Modelling of Bi-material Specimen using Extended Finite Element Discretization under  Thermo-mechanical Loading. (Bachelor’s Thesis, Indian Institute of Technology, Patna, 2015).
  • A Continuous-mesh Optimization Technique for Piece-wise Polynomial Approximation on Tetrahedral Grids (Master’s Thesis, AICES, RWTH Aachen, Germany, 2018).

 

Publications

  1. An Anisotropic H-Adaptive Strategy for Discontinuous Petrov-Galerkin Schemes using a Continuous Mesh Model
    A. Chakraborty, A. Rangarajan and G. May
    Computer & Mathematics with Applications, 2022, 106
    doi: https://doi.org/10.1016/j.camwa.2021.12.001
  2. A Residual-Based HP-Mesh Optimization Technique for Petrov-Galerkin Schemes with Optimal Test Functions
    A. Chakraborty, A. Rangarajan and G. May
    doi: http://dx.doi.org/10.23967/wccm-eccomas.2020.014
  3. A Goal Oriented Optimization Technique for Tetrahedral Grids using a Continuous- Mesh Model
    A. Rangarajan, A. Chakraborty and G. May
    AIAA Scitech 2019 Forum
    doi: https://doi.org/10.2514/6.2019-0349

 

Karsten Paul, M.Sc.

31. Oktober 2018 | von

Contact

Aachen Institute for Advanced Study
in Computational Engineering Science (AICES)
RWTH Aachen University
Schinkelstr. 2
52062 Aachen

Office: Room 431a
Phone: +49 241 80 99138
Email: paul@aices.rwth-aachen.de

LinkedIn: https://www.linkedin.com/in/karsten-paul-b7b08818b/

XING: https://www.xing.com/profile/Karsten_Paul7/cv

Education

12/2018 – 05/2022: Ph.D. Candidate, IRTG at RWTH Aachen University, Germany

04/2017 – 11/2018: Master of Science in Computational Engineering Science, RWTH Aachen University, Germany

10/2013 – 03/2017: Bachelor of Science in Computational Engineering Science, RWTH Aachen University, Germany

Professional Career

10/2017 – 07/2018: Student Assistant at fka Aachen, Germany

09/2016 – 03/2017: Intern at Volkswagen AG Brunswick, Germany

Theses

  • Phase Field Modeling of Dynamic Brittle Fracture in Thin Shells (Master Thesis, AICES, RWTH Aachen University, Germany 2018)
  • Optimization of Casting Direction as well as Positioning and Dimensioning of Feeders using an Innovative Graph-Based Target Function for the use in a Topology Optimization suitable for Casting (Bachelor Thesis, Volkswagen AG Brunswick, Germany 2017)

Publications

  1. An adaptive space-time phase field formulation for dynamic fracture of brittle shells
    based on LR NURBS
    K. Paul, C. Zimmermann, K.K. Mandadapu, T.J.R. Hughes, C.M. Landis and R.A. Sauer
    Computational Mechanics, 2020, 65, pp. 1039-1062
    doi: 10.1007/s00466-019-01807-y
  2. Isogeometric continuity constraints for multi-patch shells governed by fourth-order
    deformation and phase field models
    K. Paul, C. Zimmermann, T.X. Duong and R.A. Sauer
    Computer Methods in Applied Mechanics and Engineering, 2020, 370, pp. 113219
    doi: 10.1016/j.cma.2020.113219
  3. Dynamic Fracture of Brittle Shells in a Space-Time Adaptive Isogeometric Phase Field
    Framework
    K. Paul, T.J.R. Hughes, C.M. Landis and R.A. Sauer
    CurrentTrendsandOpenProblemsinComputationalMechanics, 2022, pp. 407-415, Springer
    Nature.
  4. An isogeometric finite element formulation for surface and shell viscoelasticity based
    on a multiplicative surface deformation split
    K. Paul and R.A. Sauer
    Preprint, https://arxiv.org/abs/2202.13413

Tim Varelmann, M.Sc.

12. Oktober 2018 | von

Contact

Aachen Institute for Advanced Study
in Computational Engineering Science (AICES)
RWTH Aachen
Schinkelstr. 2
52062 Aachen

Office: Room 424
Phone: +49 241 80 99137
Email: varelmann@aices.rwth-aachen.de

Education

11/2018 – 03/2022: Ph.D. Candidate, IRTG at RWTH Aachen University, Germany

04/2018-10/2018: Master Thesis at PSE Laboratory, Department of Chemical Engineering, MIT, USA

07/2017-04/2018: Master student at AICES Graduate School, RWTH Aachen University, Germany

Professional Career

03/2016 – 06/2016: Internship at LANXESS Deutschland GmbH, Process, Technology, Safety and Environment Department, Leverkusen, Germany

10/2014 – 03/2015: Teaching Assistant for „Material Properties“ with Prof. A. E. Ismail RWTH Aachen University, Germany

08/2012 – 09/2013: Dual Student of Business Engineering in cooperation with GE Wind Energy GmbH, Salzbergen, Germany

 

Publication

  1. A decoupling strategy for protecting sensitive process information in cooperative optimization of power flow
    T. Varelmann, J.I. Otashu, K. Seo, A .W. Lipow, A. Mitsos and M. Baldea
    AIChE Journal, 2021; e17429.
    doi: https://doi.org/10.1002/aic.17429
  2. Simultaneously optimizing bidding strategy in pay-as-bid-markets and production scheduling
    T. Varelmann, N. Erwes, P. Schäfer and A. Mitsos
    Computers and Chemical Engineering, 2022, (157), 107610
    doi: 10.1016/j.compchemeng.2021.107610
  3. Advanced feasibility cuts in decoupled cooperative optimization of power flow
    T. Varelmann, A .W. Lipow, M. Baldea and A. Mitsos
    Computers and Chemical Engineering, 2021, 107635
    doi: 10.1016/j.compchemeng.2021.107635

Cristos Psarras, M.Sc.

12. Oktober 2018 | von

Contact

Aachen Institute for Advanced Study
in Computational Engineering Science (AICES)
RWTH Aachen
Schinkelstr. 2
52062 Aachen

Office: Room 430
Phone: +49 241 80 99 142
Email: psarras@aices.rwth-aachen.de

 

Education

10/2018 – Current: Ph.D. Candidate, IRTG at RWTH Aachen University, Germany

09/2011 – 07/2017: Diploma in Electrical & Computer Engineering at AUTH   (5 year academic program – Equivalent to M.Sc.)

 

Professional Career

10/2018 – Current  Researcher at RWTH Aachen University

03/2018 – 09/2018 Software Engineer at KENOTOM

06/2017 – 03/2018 Research Associate at Center for Research & Technology Hellas

03/2017 – 05/2017 Intern at Center for Research & Technology Hellas

 

Research Interests

  • High Performance Computing
  • Automation
  • Compilers
  • Machine Learning & Computer Vision

 

Publications

  1. Linnea: Automatic Generation of Efficient Linear Algebra
    H. Barthels, C. Psarras and P. Bientinesi
    Programs. 
    ACM Trans. Math. Softw. 47, 3, Article 22 (June 2021), 26 pages.
    doi: https://doi.org/10.1145/3446632
  2. Accelerating jackknife resampling for the Canonical Polyadic Decomposition
    C. Psarras, L. Karlsson, R. Bro and P. Bientinesi
    Frontiers in Applied Mathematics and Statistics, accepted (Feb 2022)
    Preprint, arXiv:2112.03985
  3. Concurrent Alternating Least Squares for multiple simultaneous Canonical Polyadic
    Decompositions
    C. Psarras, L. Karlsson and P. Bientinesi
    ACM Transactions on Mathematical Software, accepted (Feb 2022)
    Preprint, arXiv:2010.04678
  4. The Linear Algebra Mapping Problem
    C. Psarras, H. Barthels and P. Bientinesi
    Preprint, arXiv:1911.09421
    Submitted to ACM Transactions on Mathematical Software (Sep 2021)
  5. The landscape of software for tensor computations
    C. Psarras, L. Karlsson, J. Li and P. Bientinesi
    Preprint, arXiv:2103.13756

Nicole Aretz, M.Sc.

10. Oktober 2018 | von

Contact

Aachen Institute for Advanced Study
in Computational Engineering Science (AICES)
RWTH Aachen
Schinkelstr. 2
52062 Aachen

Office: Room 421b
Tel. (0241) 80 99145
Email: aretz@aices.rwth-aachen.de

Education

10/2018 – 06/2022: Ph.D. Candidate, IRTG at RWTH Aachen University, Germany

04/2018 – 09/2018: Doctoral Student at AICES Graduate School, RWTH Aachen University, Germany

04/2016 – 03/2018: Master of Science in Mathematics, RWTH Aachen University, Germany

10/2012 – 03/2016: Bachelor of Science in Mathematics, RWTH Aachen University, Germany

 

Research Interests

  • bayesian inversion
  • optimal experimental design
  • variational data assimilation and optimal control
  • uncertainty quantification
  • model order reduction, in particular reduced basic methods
  • multilevel methods
  • parameter estimation

 

Theses

Data Assimilation and Sensor Selection for Configurable Forward Models: Challenges and Opportunities for Model Order Reduction Methods
Doctoral Thesis, IRTG-2379, RWTH Aachen, Germany, 2021

A Certified Reduced Basis Method for Parametrized 3D-VAR Data Assimilation, 
Master’s Thesis, Institut für Geometrie und Praktische Mathematik, RWTH Aachen, Germany 2018

A Space-Time Finite Element Method for Discretization of the Heat Equation,
Bachelor’s Thesis, Institut für Geometrie und Praktische Mathematik, RWTH Aachen, Germany, 2016

Puplications

  1. 3D-VAR for parameterized partial differential equations: a certified reduced basis approach
    Nicole Aretz-Nellesen, Martin A. Grepl, and Karen Veroy
    Advances in Computational Mathematics
    45, 2369-2400 (2019)
    doi: 10.1007/s10444-019-09713-w
  2. A sequential sensor selection strategy for hyper-parameterized linear Bayesian inverse problems
    Nicole Aretz-Nellesen, Peng Chen, Martin A. Grepl and Karen Veroy
    In Numerical Mathematics and Advanced Applications ENUMATH 2019 (pp. 489-497). Springer, Cham.
  3. Diffusion–reaction compartmental models formulated in a continuum mechanics framework: application to COVID-19, mathematical analysis, and numerical study
    Alex ViguerieAlessandro VenezianiGuillermo LorenzoDavide BaroliNicole Aretz-NellesenAlessia PattonThomas E. YankeelovAlessandro RealiThomas J. R. Hughes & Ferdinando Auricchio
    Comput Mech (2020), 66 (5), pp. 1131–1152
    doi: 10.1007/s00466-020-01888-0
  4. Sensor selection for hyper-parameterized linear Bayesian inverse problems
    Nicole Aretz, Peng Chen, Karen Veroy
    PAMM 20.S1 (2021)
    doi: 10.1002/pamm.202000357

     

Recorded Talks