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IEET > Staff > Research Assistants > Finn Nußbaum, M.Sc.

Finn Nußbaum

M.Sc.
Research Assistant

Contact

Finn Nußbaum, M. Sc.
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Office Hours
nach Vereinbarung
Harburger Schloßstraße 22a,
21079 Hamburg
Building Harburger Schloßstraße 22a, Room 2.017
Phone: +49 40 42878 4092
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Research Project

KoLa
Optimized Load Management and Flexibility Coordination for Electrified Urban Public Transport

KoLa

Optimized Load Management and Flexibility Coordination for Electrified Urban Public Transport

Federal Ministry for Economic Affairs and Climate Action (BMWK); Duration: 2022 to 2026

to the project page

Publications

TUHH Open Research (TORE)

2024

2023

Courses

Stud.IP
link to course in Stud.IP Studip_icon
Statistical Models (VL)
Subtitle:
This course is part of the module: Statistical Models
Semester:
SoSe 24
Course type:
Lecture
Course number:
lv3116_s24
Lecturer:
Prof. Dr. Matthias Schulte, Nihat Ay, Melina Wienkamp, Imke Christiane Bartscher, Daniela Gascon Bosqued, Ruslan Maktaew
Description:

Linear models and regression:

- Linear regression

- Nonlinear regression

- Logistic and Poisson regression

- Generalised linear models

Graphical Models and Causality:

- Conditional independence statements

- Hammersley-Clifford theorem

- Gibbs sampling

- Bayesian networks

- Causal inference

- Markov random fields

- Graphical and hierarchical models

- Applications  
Performance accreditation:
m1870-2023 - Statistical Models<ul><li>p1902-2023 - Statistical Models: Klausur schriftlich</li></ul>
ECTS credit points:
4
Stud.IP informationen about this course:
Home institute: Institut für Mathematik (E-10)
Participating institute: Institut für Data Science Foundations (E-21)
Registered participants in Stud.IP: 135
Documents: 24

Supervised Theses

ongoing

2024

  • Ahmed, Taha (2024). Development of an iterative multi-agent coordination framework for congestion prevention in low voltage grids.

  • Busch, Marcel (2024). Entwicklung eines Netzmodells zur szenarienbasierten Untersuchung von Engpässen in heutigen und zukünftigen städtischen Verteilnetzen.

  • Lindner, Joost (2024). Entwicklung einer probabilistischen Lastprognose für die Niederspannungsebene elektrischer Verteilnetze.

  • Ming, Zhao (2024). Conceptual Design for a grid demonstrator for teaching purposes and development of a suitable distribution grid simulation.

  • Wilke, Jan Jakob (2024). Definition leistungsbasierter Netzregeln zur Engpassvermeidung in elektrischen Verteilnetzen.

completed

2023

  • Kock am Brink, Jonas (2023). Entwicklung einer Engpassprognose für elektrische Verteilnetze mittels probabilistischer Verfahren.

TU Hamburg
Institute of Electrical Power and Energy Technology (ieet) E-6
Prof. Dr.-Ing. Christian Becker
Harburger Schloßstraße 36
21079 Hamburg
E-mail : ieet(at)tuhh.de
Phone : +49 40 42878 3213
Fax : +49 40 42878 2382
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