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

Publications

TUHH Open Research (TORE)

2024

2023

Courses

Stud.IP
link to course in Stud.IP Studip_icon
Cybersecurity Data Science (VL)
Subtitle:
This course is part of the module: Cybersecurity Data Science
Semester:
SoSe 24
Course type:
Lecture
Course number:
lv2914_s24
Lecturer:
Riccardo Scandariato, Ina Weigl, Dr. Nicolás Díaz Ferreyra, Catherine Tony, Torge Hinrichs, Emanuele Iannone
Description:

Theoretical Foundations:

  • Introduction to data science
  • Supervised and unsupervised learning
  • Data science methods (e.g., clustering, decision trees, artificial neural networks)
  • Performance metrics

Cybersecutrity Applications:

  • Spam detection
  • Phishing detection
  • Intrusion detection
  • Access-control prediction
  • Denial of Service (DoS) prediction
  • Vulnerability/malware prediction
  • Adversarial machine learning
Performance accreditation:
m1773-2022 - Cybersecurity Data Science<ul><li>p1760-2022 - Cybersecurity Data Science: Klausur schriftlich</li></ul><br>m1773-2023 - Cybersecurity Data Science<ul><li>p1760-2022 - Cybersecurity Data Science: Klausur schriftlich</li><li>vl440-2023 - Voluntary Course Work Cybersecurity Data Science - Subject theoretical and practical work: Subject theoretical and practical work</li></ul>
ECTS credit points:
3
Stud.IP informationen about this course:
Home institute: Institut für Software Security (E-22)
Registered participants in Stud.IP: 144
Documents: 12

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.