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Jun.-Prof. Dr. Sophie Fellenz

  • Jun.-Prof. Dr. Sophie Fellenz

    Since 2020 Sophie Fellenz is a junior professor at RPTU's department of computer science. Previously she was a research group leader at Johannes Gutenberg University Mainz (07/2020-10/2020) and before that a PostDoc in the research group of Stefan Kramer. She obtained a PhD from Uni Mainz in 2018 under the supervision of Stefan Kramer and a Magister in Philosophy and Computer Science in 2013 with a thesis on mental representation. 

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Basic Research

  • Sophie Fellenz is interested in probabilistic machine learning methods, with applications ranging from text data such as topic models to time series data. She also works on generative models and deep generative models in general. More recently, she is also interested in incorporating knowledge into neural models, for example in the form of physical equations. This results in so-called hybrid or grey-box models where data-driven models are combined with expert knowledge. Her PhD was concerned with topic models, multi-label classification, nonparametric Bayesian models and online models. 

Application related Research

  • Text data, time series data, applications in chemical engineering, scRNA data

Activities as a Reviewer

    • BMBF
    • DAAD
    • NeurIPS
    • ICML
    • ICLR
    • AISTATS
    • AAAI
    • ECML

Received Awards, Prizes, Honors

  • PRIME Research scholarship

Special Expertise

  • Basic Research

    • Machine Learning (ML): Self-Supervised Learning, Reinforcement Learning (RL), Unsupervised Learning, Anomaly Detection, Feature Engineering/Feature Extraction
    • Technology Analysis: Sociological Aspects, Economic Effects, Human-AI Interaction

  • Application related Research

    • Smart Assistant Systems: Virtual Assistants, Digital Medicine, Smart Production, Biotechnology (Biotech)
    • Autonomous Systems: Smart Automation, Bots
    • Robotics: Industrial Robots
    • Language and Text Comprehension
    • Image Recognition and Understanding: Text Recognition
    • Virtual and Augmented Reality (AR): Assistance Systems at the Workplace
    • Technology Analysis: Sociological Aspects, Technology Assessment

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