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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 > Leon Maximilian Helmich, M.Sc.

Leon Maximilian Helmich

M.Sc.
Research Assistant

Contact

Leon Maximilian Helmich
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Harburger Schloßstraße 22a,
21079 Hamburg
Building HS22a, Room 2.005
Phone: +49 40 42878 2379
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Research Project

iTherNet
Intelligent Thermal Networks - New cooling technologies and energy-optimized operating concepts

iTherNet

Intelligent Thermal Networks - New cooling technologies and energy-optimized operating concepts

 Federal Ministry for Economic Affairs and Climate Action (BMWK); Duration: 2020 - 2023

to the project page

Publications

TUHH Open Research (TORE)

2023

2021

Courses

Stud.IP
zur Veranstaltung in Stud.IP Studip_icon
Machine Learning in Electrical Engineering and Information Technology
Semester:
SoSe 24
Veranstaltungstyp:
Vorlesung (Lehre)
Veranstaltungsnummer:
lv3004_s24
DozentIn:
Prof. Dr. sc. techn. Christian Schuster, Prof. Dr.-Ing. Christian Becker, Prof. Dr. Alexander Kölpin, Gerhard Bauch, Dr. Maximilian Stark, Dr. Davood Babazadeh, Dr. Cheng Yang, PD Dr.-Ing. habil. Rainer Grünheid, Simon Stock, M.Sc.
Beschreibung:
This master course, a collaborative effort between the Institute of Communications, the Institute for High-Frequency Engineering, the Institute for Power Systems, and the Institute for Theoretical Electrical Engineering, is designed to unveil the synergies between machine learning and our respective fields of expertise. In an age defined by rapid technological advancement, machine learning stands as a catalyst for innovation, offering transformative possibilities across diverse sectors. From optimizing communication systems to enhancing power grid efficiency, and from refining signal processing techniques to enabling autonomous systems, the integration of machine learning techniques holds immense promise for addressing contemporary challenges. Throughout this course, we will delve into the theoretical underpinnings, practical methodologies, and tangible applications of neural networks and machine learning algorithms. By delving into algorithmic design, data analysis, and optimization techniques, we aim to equip you with the skills and insights needed to navigate the complexities of modern engineering landscapes.
Leistungsnachweis:
m1785-2022 - Machine Learning in Electrical Engineering and Information Technology<ul><li>p1778-2022 - Machine Learning in Electrical Engineering and Information Technology: mündlich</li></ul>
ECTS-Kreditpunkte:
6
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Institut für Nachrichtentechnik (E-8)
In Stud.IP angemeldete Teilnehmer: 99
Anzahl der Postings im Stud.IP-Forum: 4
Anzahl der Dokumente im Stud.IP-Downloadbereich: 25

Supervised Theses

ongoing

2024

  • Eberhard, F. (2024). Estimating AC and DC losses in the inductor of a switch mode power supply..

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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