Johannes Krotz | Computational Methods | Best Researcher Award

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Dr. Johannes Krotz | Computational Methods | Best Researcher Award

Postdoctoral Fellow at Notre Dame, United States

πŸ‘¨β€πŸŽ“ Profiles

🌟Summary

πŸ‘¨β€πŸŽ“ PhD candidate in Mathematics with a minor in Computer Science, specializing in probabilistic and data-driven methods for numerical PDEs and hybrid Monte Carlo methods for complex systems simulations. Experienced in statistical modeling, computational physics, and advanced simulations with a strong background in teaching and academic leadership. Currently working as a Postdoctoral Researcher at the University of Notre Dame.

πŸŽ“ Education

πŸŽ“ PhD in Mathematics (Minor in CS)
University of Tennessee Knoxville, 2021–2024

  • Dissertation on Probabilistic & Data-Driven Methods in Numerical PDEs
  • GPA: 4.0

πŸ“Š M.Sc. in Statistics
University of Tennessee, 2022–2024

  • GPA: 3.9

πŸ“š M.Sc. in Mathematics
Oregon State University, 2019–2021

  • GPA: 4.0

βš›οΈ M.Sc. in Physics
University of Konstanz, 2015–2019

  • GPA: 4.0 (Honors)

πŸ”’ B.Sc. in Mathematics & Physics
University of Konstanz, 2012–2018

  • GPA: 3.5 (Mathematics), 3.3 (Physics)

πŸ’Ό Professional Experience

πŸ”¬ Postdoctoral Researcher
University of Notre Dame, 2024–Present

  • Research on hybrid Monte Carlo & deterministic kinetic transport algorithms for exascale simulations in neutron transport.

πŸ§‘β€πŸ’» Graduate Research Assistant (GRA)
University of Tennessee/ORNL, 2023–2024

  • Advancing dynamic likelihood filters for stochastic advection-diffusion equations in collaboration with ORNL and UTK.

πŸ’Ό Research Intern
Oak Ridge National Lab (ORNL), 2021–2022

  • Developed hybrid algorithms for simulating complex particle systems in 2D & 3D.

🌍 Research Intern
Los Alamos National Lab (LANL), 2020

  • Focus on high-fidelity discrete fracture networks and Poisson-disk sampling algorithms for triangulations.

πŸ”¬ Research Interests

  • 🧠 Computational Mathematics: Hybrid Monte Carlo methods, kinetic transport equations, and numerical simulations for complex physical systems.
  • πŸ” Stochastic Processes: Advanced data-driven filtering techniques and applications in fluid dynamics, advection-diffusion, and PDEs.
  • πŸ’» Statistical Modeling: Development of methods for high-dimensional data and stochastic modeling.
  • 🌐 Interdisciplinary Work: Collaborating across fields of mathematics, physics, and engineering to tackle real-world computational challenges.

πŸ† Awards

  • 1st & 3rd place at the UTK SIAM Research Showcase (2023, 2024)
  • Randall E. Cline Award (2022) for research excellence

πŸ–₯ Technical Skills

  • Python, C++, R, Matlab, LATEX, and more
  • Basic Fortran, AWK

πŸ”— Professional Memberships

  • SIAM, AWM, AAAS, UCW

 Publications

A Hybrid Monte Carlo, Discontinuous Galerkin Method for Linear Kinetic Transport Equations

  • Authors: Johannes Krotz, Cory D. Hauck, Ryan G. McClarren
  • Journal: Journal of Computational Physics, Vol. 514
  • Year: 2024
Variable Resolution Poisson-Disk Sampling for Meshing Discrete Fracture Networks
  • Authors: Johannes Krotz, Matthew R. Sweeney, Jeffrey D. Hyman, Juan M. Restrepo, Carl W. Gable
  • Journal: Journal of Computational and Applied Mathematics, Vol. 407
  • Year: 2022
Dynamic Likelihood Filters for Advection Diffusion Equations
  • Authors: Johannes Krotz, Jorge M. Ramires, Juan M. Restrepo
  • Journal: The Monthly Weather Review
  • Year: Under review
Minimizing Effects of the Kalman Gain on Posterior Covariance Eigenvalues, the Characteristic Polynomial and Symmetric Polynomials of Eigenvalues
  • Authors: Johannes Krotz
  • Journal: Arxiv (preprint)
  • Year: 2024