cv

Basics

Name Anna Penzkofer
Label PhD Candidate
Email anna.penzkofer@vis.uni-stuttgart.de
Url https://apenzko.github.io/

Work

  • 2023.02 - present

    Stuttgart, Germany

    PhD Candidate
    Institute for Visualisation and Interactive Systems, University of Stuttgart
    Part of research group Human-Computer-Interaction and Cognitive Systems led by Prof. Dr. Andreas Bulling
    • Interactive Behaviour
    • Computer Vision
    • Reinforcement Learning
  • 2021.02 - 2022.03

    Munich, Germany

    Working Student -- Perception & Cognition
    German Aerospace Center (DLR)
    Part of perception & cognition group, working on semantic segmentation for real-time navigation robot Rollin' Justin. Collaboration on open-source tool Blender-Proc https://github.com/DLR-RM/BlenderProc.
  • 2019.10 - 2020.12

    Munich, Germany

    Working Student -- Data Analytics
    Siemens AG
    Preprocess and analyze project data, implement data augmentation and fit forecasting for classification models.
  • 2018.11 - 2019.08

    Stuttgart, Germany

    Research Assistant -- Machine Learning
    University of Stuttgart
    Conduct research on learning-based gaze estimation as well as image synthesis such as gaze redirection and generative adversarial networks, including testing state-of-the-art methods, analyzing and developing new models.

Education

  • 2020.04 - 2022.12

    Munich, Germany

    Masters
    Technical University Munich
    Computer Science
    • Cognitive Systems
    • Machine Learning for Computer Vision
    • Reinforcement Learning for Robotics
  • 2017.10 - 2020.03

    Stuttgart, Germany

    Bachelors
    University of Stuttgart
    Computer Science
    • Artificial Intelligence
    • Machine Learning
    • Computer Vision

Certificates

Reinforcement Learning
University of Alberta 2024-02-26

Publications

  • Oct 2021
    ConAn: A Usable Tool for Multimodal Conversation Analysis
    International Conference on Multimodal Interaction (ICMI)
    ConAn is a software tool that integrates multimodal analyses on 360 degree videos of conversations and displays them in a useable graphical user interface (GUI). Modalities include eye gaze, body pose, facial expressions, speaking activity and object tracking.
  • June 2023
    Int-HRL: Towards Intention-based Hierarchical Reinforcement Learning
    Adaptive and Learning Agent Workshop (ALA)
    Proposes new method Intention-based Hierarchical Reinforcement Learning (Int-HRL). Tested on the long-horizon, sparse reward task Montezuma's Revenge from the Atari2600 game suite.

Languages

German
Native speaker
English
Fluent