Dr. Monika Eisenmann

Biography

Monika Eisenmann is a Senior Lecturer at Lund University, specializing in Applied Mathematics. Her research primarily focuses on stochastic numerical analysis, particularly in the application of stochastic differential equations and randomized algorithms. These areas encompass the development of numerical methods that address uncertainties and natural variability in models, leveraging stochastic elements to efficiently solve high-dimensional problems. Eisenmann's work involves employing Monte Carlo algorithms to demonstrate the effectiveness of randomization in optimization, a crucial aspect in machine learning. Additionally, she is involved in developing numerical approximation techniques for stochastic processes and analyzing specific applications in optimization problems. Over the past few years, she has led collaborative projects centered on moving domain decomposition methods for parabolic PDEs and optimization methods that arise in machine learning. Her contributions extend to mentoring PhD students, where she supports their academic pursuits in advanced mathematics and related fields.

Research Interests

Experience