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Institute of Electrical Power and Energy Technology
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Institute of Electrical Power and Energy Technology
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IEET > Staff > Research Assistants > Anna-Lena Steen, M.Sc.

Anna-Lena Steen

M.Sc.
Research Assistant

Contact

Anna-Lena Steen, M. Sc.
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Office Hours
nach Vereinbarung
Harburger Schloßstraße 22a,
21079 Hamburg
Building HS22a, Room 2.017
Phone: +49 40 42878 4091
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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

2022

Courses

Stud.IP
zur Veranstaltung in Stud.IP Studip_icon
Seminare.EIM: Introduction to Deep Learning (DSBS, CSMS, IIWMS, TMBS, IMPICS)
Semester:
SoSe 24
Veranstaltungstyp:
Seminar (Lehre)
DozentIn:
Dr. rer. nat. Pradeep Banerjee
Beschreibung:
Deep Learning is one of the most vibrant areas of modern machine learning, offering one of the most promising routes to advancing Artificial Intelligence (AI). Deep Learning systems are reshaping the AI landscape across various fields, including language comprehension, speech and image recognition, and autonomous driving. This seminar covers deep neural networks basics and their applications in various AI tasks. We will explore several key paradigms related to expressivity, optimization and generalization properties of modern deep learning systems. Students will gain proficiency in Deep Learning, enabling them to apply it to different scenarios and comprehend current literature in the field.
TeilnehmerInnen:
This seminar is aimed at all Bachelor- and Master- level students in the Informatik and the Techno-Mathematik courses. A maximum of 12 students can participate in the seminar.
Voraussetzungen:
As a prerequisite, this seminar will assume familiarity with basic calculus, linear algebra, and probability. Familiarity with a programming language such as Python is desirable.
Lernorganisation:
The seminar is divided into six blocks (following an introductory session), each lasting two weeks. Every block consists of the following components: * Week 1: Preparation of a presentation using prescribed sources (book chapters, video lectures, scientific articles). * Week 2: Presentations by 2 participants, each lasting 25 minutes based on a topic assigned to each participant in the first session of the seminar.
Bereichseinordnung:
Studiendekanat Elektrotechnik, Informatik und Mathematik
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Studiendekanat Elektrotechnik, Informatik und Mathematik (E)
beteiligte Institute: Institut für Data Science Foundations (E-21)
In Stud.IP angemeldete Teilnehmer: 9
Anzahl der Dokumente im Stud.IP-Downloadbereich: 5

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.

  • Krammer, Friederike (2024). Entwicklung eines Algorithmus zur Koordinierung flexibler Prosumer zur Netzengpassvermeidung in Niederspannungssträngen.

  • Möller, Julius (2024). Untersuchung von Kennzahlen zur Bewertung der Diskriminierungsfreiheit von Engpassmanagementmaßnahmen.

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

completed
TU Hamburg
Institute of Electrical Power and Energy Technology (ieet) E-6
Prof. Dr.-Ing. Christian Becker
Harburger Schloßstraße 22a
21079 Hamburg
E-mail : ieet(at)tuhh.de
Phone : +49 40 42878 3213
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