Valeriy Avanesov, Christian Bayer, Michele Coghi, Pavel Dvurechensky, Andzhey Koziuk, Peter Mathé, Mario Maurelli, Hans-Joachim Mucha, Paolo Pigato, Jörg Polzehl, Martin Redmann, John G. M. Schoenmakers, Benjamin Stemper, Alexandra Suvorikova, Karsten Tabelow
The research group
Stochastic Algorithms and Nonparametric Statistics focuses on two areas of mathematical research, Statistical data analysis and Stochastic modeling, optimization, and algorithms. The projects within the group are related to timely applications mainly in economics, financial engineering, life sciences, and medical imaging. These projects contribute in particular to the main application areas Optimization and control in technology and economy and Quantitative biomedicine of the WIAS.
Specifically, the mathematical research within the group concentrates on the
- modeling of complex systems using methods from nonparametric statistics,
- statistical learning,
- risk assessment,
- valuation in financial markets using efficient stochastic algorithms and
- various tools from classical, stochastic, and rough path analysis.
The research group hosts the focus plattform
- The new CRC 1294 "Data assimilation" has been approved with Prof. Dr. M. Opper (TUB), Prof. Dr. S. Reich (UP), and Prof. Dr. V. Spokoiny heading the project "A06 Approximative Bayesian inference and model selection for stochastic differential equations (SDEs)".
- Prof. Peter K. Friz (TU Berlin/WIAS) received the ERC Consolidator Grant
Geometric aspects in pathwise stochastic analysis and related topicsrunning from 2016 to 2021. [>>more]
- Dr. Th. Koprucki (RG1) and Dr. K. Tabelow (RG6) receive funding for the ECMath-project OT7 "Model-based geometry reconstruction of quantum dots from TEM" running from 06/2017-12/2018. [>>more]
- Dr. J. Schoenmakers and Prof. Dr. Spokoiny receive funding for the ECMath-project "Decisions in energy markets via deep learning and optimal control" running from 06/2017-12/2018.
- New publication: J. Polzehl, K. Tabelow, Low SNR in diffusion MRI models, J. Amer. Statist. Assoc., 111 (2016) pp. 1480-1490, DOI 10.1080/01621459.2016.1222284.
- Partial Differential Equations
- Laser Dynamics
- Numerical Mathematics and Scientific Computing
- Nonlinear Optimization and Inverse Problems
- Interacting Random Systems
- Stochastic Algorithms and Nonparametric Statistics
- Thermodynamic Modeling and Analysis of Phase Transitions
- Nonsmooth Variational Problems and Operator Equations