Credit: privat
Jacob Heieck, M.Sc.
Room C 305
Tel.: +49 621 181 2564
E-Mail: jacob.heieckuni-mannheim.de
Research Interests
- Application of (Quasi) Monte-Carlo Methods
- Mathematical Analysis of Stochastic Particle Systems governed by Stochastic Differential Equations
- Mathematical Optimization
Short CV
- since 09/
2023: Research Assistant, School of Business and Mathematics, University of Mannheim - 08/
2021 – 08/ 2023: M.Sc. in Business Mathematics, University of Mannheim - 09/
2022 – 02/ 2023: Erasmus stay at Universitat Politecnica de Catalunya (UPC), Spain - 09/
2018 – 07/ 2021: Studies in Business Mathematics, University of Mannheim - 07/
2017: Graduated from Schillerschule in Frankfurt a. M. (Abitur)
Publications
- S. Göttlich, J. Heieck, A. Neuenkirch – Using low-discrepancy points for data compression in machine learning: an experimental comparison, accepted to SpringerOpen, Journal of Mathematics in Industry, January 2025
Conferences and Workshops
- Speaker and Participant at the Summer School Numerical Methods for High-Dimensional Data in Rome, September 2025; Talk: Analytical and Numerical Perspectives on Exponential Stability in Finite-N Consensus-Based Optimization
- Speaker at the 10th Workshop on High-Dimensional Approximation (HDA) in Bonn, September 2025; Talk: Exponential Stablitiy of Finite-N Consensus-Based Optimization
- Invited Speaker at the Stochastic Numerics and Inverse Problems (SNIPS) Conference in Växjö, August 2025; Talk: Deterministic and Stochastic Dynamics in Finite-N Consensus-Based Optimization
- Participant in the 10th GAMM Juniors Summer School: Model Order Reduction (MOR) in Dresden, July 2025
- Participant in the Summer School on Optimization, Uncertainty and AI (TRR154) in Hamburg, August 2024
- Participant in the Summer school on fundamentals and applications of diffusion models in London, June 2024
Teaching
- HWS 2025: Numerics (Programming Exercise)
- HWS 2025: Development of a Python Programming Course for Bachelor Students (Buisness Mathematics)
- FSS 2025: Monte-Carlo Methods (Exercise)
- HWS 2024: Numerics (Programming Exercise & Substitute Lecturer)
- FSS 2024: Analysis for Business Informatics (Exercise)
- FSS 2024: Seminar: Modeling, Numerics, and Optimization (Tutor)
- HWS 2023: Seminar: Modeling, Numerics, and Optimization (Tutor)
- HWS 2023: Linear Optimization (Tutorial)
- FSS 2022: Nonlinear Optimization (Exercise)
- HWS 2021: Linear Optimization (Tutorial)