Prof. Dr. Erik Rodner

Portrait von Prof. Dr. Erik Rodner
 +49 30 5019-4362
Erik.Rodner@HTW-Berlin.de
Campus Wilhelminenhof
WH Gebäude C , 115
Wilhelminenhofstraße 75A
12459 Berlin

Lehr- und Forschungsgebiet

Informatik,
Maschinelles Lernen,
Datenanalyse,
Vernetzte Systeme,
IoT,
Bildverarbeitung,
KI/Künstliche Intelligenz (Computer Science - Machine Learning - Data Science - Distributed Systems - IoT - Computer Vision - Artificial Intelligence)

Schwerpunkte

Deep Learning, Zeitreihenanalyse, Interaktives Lernen von Modellen, Datenanforderungen von ML-Methoden, Lernen unter Daten- und Annotationsmangel (Deep Learning, Time Series Analysis, Interactive Learning of Models, Data requirements for Machine Learning, Learning with Data and Annotation Scarcity)

Homepage

http://www.erodner.de

Forschungsaktivitäten

Werdegang

Erik Rodner is a researcher in the field of computer vision and machine learning, and his work focuses on developing algorithms and models to enable machines to understand and interpret visual data. Some of his research contributions include the development of deep learning architectures for object recognition and semantic segmentation, the use of weakly-supervised and self-supervised methods to improve annotation efficiency, and the integration of domain-specific knowledge to improve the robustness of vision systems. His research has been published in several well-respected journals and conferences. Overall, Erik Rodner's research aims to push the boundaries of what machines are capable of perceiving and understanding from visual data, and to make these capabilities more widely available for practical applications.

Sprechzeiten

Termine können jederzeit per e-Mail vereinbart oder Calendly (https://calendly.com/rodner/sprechstunde) vereinbart werden // Please contact me by e-mail or use the calendly link above to arrange a meeting.

Funktion und Organisationseinheit

  • Ingenieurinformatik (B)
    Hochschullehrer*in, Praktikumsbeauftragte*r
  • Informatik in Ingenieurwissenschaften (M)
    Hochschullehrer*in
  • Fachbereich 2: Ingenieurwissenschaften - Technik und Leben
    Hochschullehrer*in