Applied Machine Learning

The Applied Machine Learning group is dedicated to advancing the theory and application of machine learning and deep learning methodologies tailored for real-world challenges. Our research focuses on real-world data, often derived from diverse sources such as time series, visual content, text, sensor measurements, or system logs. We investigate the properties of deep learning models, focusing on critical aspects such as robustness to distribution shifts, efficiency, privacy, and explainability. We aim to create scalable and interpretable solutions that enhance decision-making across various domains.

 

Group Head

Dr. Dario Zanca

Raum: Room 01.016

Group Members

Students

If you are interested in writing a Bachelor’s or Master’s thesis in our group, please check the lab’s Student Theses and Jobs.

    • Nils Steinlein
      The creation and evaluation of a video-based polar bear Re-Identification dataset on current Re-ID methods
    • Sara Zarifi
      Lynx Re-Identification from Camera Trap Images in the Wild

     

    Projects

    2025

    2024

    2023

    2022

    2021

    2020

    2019

    2017

    2016

    2015