Alexander Vogler,

Dr.rer.nat.

vogler@math.tu-berlin.de

About me

I am a PhD mathematician with strong expertise in stochastic control theory and the development of (AI-based) optimization algorithms. A central focus of my research lies in optimal control of mean-field/reaction-diffusion models within the realm of computational neuroscience and the efficient numerical implementation of optimization algorithms in Python. I possess a strong proficiency in Python and am particularly adept with various tools such as TensorFlow, NumPy, and SciPy.

Research Interest

I am mainly interested in the numerical approximation of optimal controls for Mean-Field S(P)DEs, with a focus on approximations using artificial neural networks. Of particular interest to me are Mean-Field models arising in computational neuroscience.

Education

  • 2023 - Ph.D. in Mathematics, Technical University of Berlin
  • 2019 - M.Sc. in Mathematics, Technical University of Berlin
  • 2016 - B.Sc. in Mathematics, Technical University of Berlin

Research Fields

  • Mean-Field stochastic (partial) differential equations
  • Stochastic control in infinite dimensions
  • Numerical approximation
  • Machine Learning