Reliably extracting information from large datasets and appropriately accounting for uncertainties in the description of processes are two significant challenges in our modern society. Addressing such challenges requires an increasing combination of analysis, optimisation, and numerics with probability theory and statistics; a combination that characterises research at the WIAS.



At the Weierstrass Institute, sophisticated, mathematically consistent models of real world systems are developed. These models enable the application of powerful analytical techniques and then, through an effective numerical implementation, the performance of reliable simulation and optimization studies of the underlying complex problems.


Mathematical Core Areas

The WIAS is organised in eight research groups specializing in different mathematical techniques and methods. Additional temporary teams are created as the need arises. The core areas of mathematical research are the analysis and numerics of partial differential equations, and stochastics.


Cooperation and Consulting

Modern applied mathematical methods are a fundamental resource and driving force for technological and economic development around the world. The rapid development of computer technology and mathematically based numerical methods are making it possible to numerically simulate ever more complex engineering, medical, economic and environmental problems.

At the WIAS excellent fundamental research is combined with years of experience in cooperating successfully with partners in the widest possible mix of application fields. The institute is therefore a recognized expert in the solution of complex economic, scientific, and technical problems by means of mathematical modeling and numerical simulation.



TIB Hannover and WIAS organize 2nd Leibniz MMS Days
The second annual meeting of the Leibniz Network “Mathematical Modelling and Simulation” (MMS) will take place from February 22 to February 24, 2017 in Hannover.


Upcoming Event
Tuesday, 21.02.2017, 15.00 (WIAS-406)
Seminar Modern Methods in Applied Stochastics and Nonparametric Statistics
A. Locatelli, Universität Potsdam:
Adaptation to noise parameters in non-parametric active learning

further events


Head of the Department Computer Technology and IT unit manager (17/02)

Research Assistant Position (17/03)