Prof. Dr. Jana Schor

(née Hertel)

Head of Bio-Data Science

Helmholtz Centre for Environmental Research - UFZ
Department Computational Biology
Permoserstr. 15
04318 Leipzig
GERMANY

Building: Building 4.1
Room: Room 238
Phone: +49 341 235 4779
Email: jana.schor@ufz.de



Curriculum Vitae

Current position

Head of Bio-Data Science Group, Department Computational Biology and Chemistry

Professorship

Bio-Data Science, Faculty of Mathematics and Computer Science, University of Leipzig, Germany

Previous position

Head of Bioinformatics, Department Computational Biology

Scientific degrees

  • Professorship Bio-Data Science (2024)
  • PhD Computer Science / Bioinformatics (2008)
  • Diploma Computer Science (2005)

Research:

My research centers on advancing Data Science methodologies—such as Statistical, Machine, Deep Learning, and Data Analysis and Integration—to unlock deeper insights from expansive Big Data in human and environmental health. By developing and applying cutting-edge computational techniques, I aim to broadly generate novel hypotheses and predictive models, particularly within ecological and health research domains. A core focus of my work is to bolster the credibility of AI-driven analyses by embedding explainability and quantifiable uncertainty measures into each application. Additionally, I strongly emphasize reproducible research, ensuring that findings are transparent, consistent, and valuable for the scientific community.

  • Data integration and analysis via graph databases
  • Graph neural networks, explainability, and quantification of uncertainty to improve computational predictions
  • Grounding LLMs with domain-specific knowledge graphs for enhanced data accessibility

Infrastructure, programs and approaches:

  • High-performance computing clusters for large-scale data processing.
  • Training AI on GPUs to accelerate model performance.
  • Graph and other neural networks for complex, interconnected data structures (for supervised, unsupervised, and reinforcement learning tasks).
  • Knowledge graphs and graph databases for data organization and semantic relationships.
  • Large language models to enhance interpretability and applications in research.
  • Programming languages like R, Python, shell scripting, awk, Cypher, and SQL for versatile data manipulation and analysis.

Teaching and educational offers:

In addition to my research, I am dedicated to teaching future data scientists and computer science students. Via the university Leipzig, I offer courses in statistical learning, R programming, and an interactive Data Science curriculum designed to prepare students comprehensively for the field. These courses include:

  • Hands-on training in R and Python,
  • Version control with Git,
  • Agile project and self-management practices,
  • Storytelling with data,
  • Crafting compelling and representative visuals and
  • Developing strong presentation skills.
  • I aim to equip students with a robust, practical skill set that prepares them for success in real-world data science roles.


Helmholtz AI - Artificial intelligence cooperation unit
Helmholtz AI associates extend the network for applied AI researchers within the Helmholtz Association to leverage the breadth of activities and strengths of our AI research.
HIDA - HH information & data science academy
The Helmholtz Information and Data Science Academy (HIDA) offers extensive training in Information and Data Science to doctoral researchers and postdocs.


Publications

My five recent most essential publications are sorted by relevance:

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2025 (4)

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2024 (4)

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2023 (2)

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2022 (4)

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2021 (2)

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2020 (3)

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2019 (3)

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2018 (1)

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2017 (2)

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2016 (5)

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For older publications processed at the Uni Leipzig and/or Uni Wien under my birth name Jana Hertel

Professur für Bioinformatik
Institut für Informatik
Universität Leipzig
Härtelstr. 16-18
D-04107 Leipzig

Institut für Theoretische Chemie
Universität Wien
Währinger Straße 17
A-1090 Wien

please refer to my ORCID profile.