Transforming the World
MATH+ funds six positions for heads of independent junior research groups in application-driven basic mathematical research, in order to strengthen support for excellent young researchers who already have some years of postdoc experience, and to give them a head start in building their own research profile and group within the supportive environment of a large Cluster of Excellence.
Application-driven Random and Multiscale Dynamics
Maximilian Engel took up his position as head of the MATH+ Junior Research Group “Application-
driven random and multiscale dynamical systems” at FU Berlin in July 2020. His research concerns various areas within Dynamical Systems, including random dynamical systems and their parameter-dependent change (bifurcations) as well as fast-slow ODEs, SDEs and PDEs, in particular those with non-hyperbolic singularities. Additionally, he is working on stochastic models in population dynamics, with an increased focus on game theory and (chemical) reaction networks.
Maximilian Engel studied mathematics, economics, and philosophy at LMU Munich, Munich School of Philosophy, and Imperial College London. He received his Ph.D. in mathematics from Imperial College London in February 2018, under the supervision of Jeroen Lamb and Martin Rasmussen. Afterward, he held a Postdoc position at TU Munich within the DFG CRC 109 “Discretization in Geometry and Dynamics”, working with Christian Kuehn.
Data-Driven Computational Optimization
Aswin Kannan took up his position as head of the MATH+ Junior Research Group “Data-Driven Computational Optimization” at HU Berlin in October 2021. His research targets efficient deployment of mathematical optimization to build machine learning models. Applications of interest span from Engineering and Computational Biology to Smart Energy Usage and Imaging. He also works on Derivative Free Optimization and Variational Inequalities.
Prior to joining MATH+, he had worked for IBM Labs as a Research Staff Member in India (2015-2021). Even earlier, he had worked for Argonne National Labs and Oracle Analytics (both in the United States). He holds a Doctorate from Penn State (United States), a Masters from University of Illinois at Urbana Champaign (United States), and a Bachelors from College of Engineering Guindy, Chennai, India.
Optimization Under Uncertainty
Guillaume Sagnol took up his position as Head of the Junior Research Group “Optimization under Uncertainty” at TU Berlin in February 2017 (originally as ECMath/MATHEON JRG, then since January 2019 as MATH+ JRG).
His research is at the interface of discrete optimization, convex conic programming, and statistics.
Guillaume Sagnol obtained his master degree in science and engineering at École des Mines de Paris in 2007, followed by his PhD in 2010 at INRIA Saclay & CMAP (École Polytechnique). From 2010 – 2014 he was postdoctoral researcher at ZIB, then from 2014 – 2016 at Charité, and 2016 – 2017 again at ZIB.
Statistical Inversion and Quantification of Uncertainties
Fabian Telschow took up his position as head of the MATH+ Junior Research Group “Statistical Inversion and Quantification of Uncertainties” at HU Berlin in March 2021.
In his research he developes statistical methodologies for image analysis and functional data using random field theory. His focus lies on inferential methodologies such as confidence sets for random fields on irregular domains in arbitrary dimension and related topics such as quantification of stochastic uncertainties of level sets. With the group of Thomas Nichols (University of Oxford) he applies these methods to neuro-imaging data. Further applications comprise for example biomedical gait data and climate data.
Fabian Telschow studied mathematics and physics at the Georg-August-University Göttingen and received his Ph.D. in mathematical statistics from Georg-August-University Göttingen in September 2016, under supervision of Stephan Huckemann and Axel Munk. Afterward, he held a Postdoc position at University of California, San Diego, working with Armin Schwartzman.
Mathematics for sustainability transitions
Since December 2019, Sarah Wolf is Head of the MATH+ Junior Research Group “Mathematics for Sustainability Transitions“ at FU Berlin. Her main research interest is a mathematical foundation for empirical agent-based modeling and simulation to address societal challenges. Application topics include a macroeconomic sustainability transition as envisaged by the European Green Deal and a sustainable mobility transition, but also models of epidemic spreading. A complementary research interest is the Decision Theatre – a dialogue format for involving stakeholders and citizens in the research process.
Sarah Wolf studied mathematics at HU Berlin. Since her PhD studies at the Potsdam Institute for Climate Impact Research and FU Berlin, her research has been interdisciplinary. She has worked on economic and agent-based modeling in the context of Green Growth and sustainable mobility as well as the Decision Theatre at the Global Climate Forum, where she remains a Board Member.