Welcome to the group “Mathematics in Computational Science and Engineering (MATHICSE-Group)
The group of Mathematics in Computational Science and Engineering includes the Chair of Computational Mathematics and Numerical Analysis (ANMC), the Chair of Modelling and Scientific Computing (CMCS), the Chair of Numerical Algorithms and High Performance Computing (ANCHP), the Chair of Scientific Computing and Uncertainty Quantification (CSQI), the Chair of Computational Mathematics and Simulation Science (MCSS), the Chair of Numerical Modelling and Simulation (MNS) and the group of Professor M. Picasso (GR-PI).
Promote at the highest scientific level the research and education on mathematical modeling, numerical modeling, algorithmic development and simulation, as well as their application in nature, environment, life, society, science and engineering. Establish and lead research programs in Computational Science and Engineering within the Institute of Mathematics and interact with existing projects in the CSE area across the EPFL Campus.
Big data and uncertainty quantification: statistical inference and information-theoretic techniques applied to computational chemistry
An incentive to use coarse-grained models is to use them for inference and control instead of the original (often intractable) model. Since coarse-grained models are always “wrong”, questions such as inference under model misspecification or goal-oriented uncertainty quantification (e.g. for control) come into play. This workshop will address such topics, with a special focus on predictive modelling, uncertainty quantification in molecular simulation and sensitivity analysis.
26 to 29 March 2019 - CIB premises (Room GA 3 21).
1 to 3 April 2019 - CECAM premises (Room BCH 3113).
Part of the Semester : Multi-scale Mathematical Modelling and Coarse-grain Computational Chemistry
By: Carsten Hartmann, BTU Cottbus-Senftenberg Fabio Nobile, EPFL Frank Pinski, University of Cincinnati Tim Sullivan, Zuse Institute Berlin
Thesis Director: Prof. A. Abdulle
Mathematics doctoral program
Thesis Nr. 9360
By: Andrea DI BLASIO
By: Yves Revaz, Laboratory of Astrophysics, EPFL
Prof. Annalisa Buffa awarded the ERG Adcanced Grant CHANGE, “New CHallenges for (adaptive) PDE solvers: the interplay of ANalysis and Geometry”. Host Institution: Ecole Polytechnique Federale de Lausanne (EPFL). Addition Beneficiaries: Consiglio Nazionale Della Ricerche Istituto di Matematica Applicata e Technologie Informatiche “E. Magenes” (CNR-IMATI); Universitat Linz Johannes Kepler University (JKU-LINZ); Oesterreichische Akademie des Wissenschaften Johann Radon Institute for Computational and Applied Mathematics (RICAM)
ECCOMAS Award for the best PhD Thesis in 2016 to Dr D. Guignard (GR-PI & CSQI, EPFL)
Dr. Diane Guignard, member of the Chair of Scientific Computing and Uncertainty Quantification and the Group Picasso, Institute of Mathematics, EPFL, has been awarded the ECCOMAS Award for for one of the two best PhD Theses in 2016, for her PhD Thesis entitled “A posteriori error estimation for partial differential equations with random input data” (EPFL thesis #7260, 2016). The European Community on Computational Methods in Applied Sciences (ECCOMAS) attributes the award to highlight outstanding achievements of two young persons at the start of their scientific careers; the awards will be handed over at the ECCOMAS Young Investigator Conference – YIC 2017, Milan, Italy, September 13 – 15. PPP
Many congratulations to Diane!
ECCOMAS Award for the best PhD Thesis in 2015 to Dr. F. Negri (CMCS, EPFL)
Dr. Federico Negri, member of the Chair of Modelling and Scientific Computing, MATHICSE, SB, EPFL, has been awarded the ECCOMAS Award for one of the two best PhD Theses in 2015. The European Community on Computational Methods in Applied Sciences (ECCOMAS) attributes the award to highlight outstanding achievements of two young persons at the start of their scientific careers; the award will be handed over at the ECCOMAS 2016 Conference in Crete, Greece, June 5 – 10.
The thesis of Dr. Negri, titled “Efficient Reduction Techniques for the Simulation and Optimization of Parametrized Systems: Analysis and Applications” (EPFL thesis #6810, 2015) and developed under the supervision of Prof. A. Quarteroni and Prof. G. Rozza, has been awarded the prize for its outstanding contributions in developing an efficient Reduced Basis method for the high fidelity solution of computationally-intensive problems described by Partial Differential Equations, with application to blood flows, mass transport, and control.
Many congratulations to Federico!