Stefan Oehmcke
Tenure-track Assistant Professor for Visual and Analytic Computing in Ocean Technologies
Research Profile
- Machine learning for spatio-temporal and multi-modal data.
- Earth observation for environmental monitoring, including forests, agriculture, wetlands, drylands, and fire vulnerability.
- Maritime and ocean-technology applications, including marine time series, virtual sensors, and visual analytics.
- Representation learning, self-supervised learning, hybrid modelling, and efficient inference under data and resource constraints.
Current Positions
Tenure-track Assistant Professor, University of Rostock, Institute for Visual and Analytic Computing, Germany
10-2024 - Present
Chair of Visual and Analytic Computing in Ocean Technologies
Assistant Professor, University of Copenhagen, Department of Computer Science, Denmark
12-2023 - Present (secondary employment)
Academic Career
Assistant Professor, University of Copenhagen, Department of Computer Science, Denmark
12-2022 - 11-2023
- PerformLCA
- Teaching in Data Science Lab
PostDoc, University of Copenhagen, Department of Computer Science, Denmark
12-2020 - 11-2022
- DeReEco: Deep Learning and Remote Sensing for Unlocking Global Ecosystem Resource Dynamics
- FirePrev: Aid to Prioritize Fire Prevention Efforts
- Monitoring Changes in Big Satellite Data via Massively-Parallel Artificial Intelligence
PostDoc, University of Copenhagen, Department of Computer Science, Denmark
12-2018 - 11-2020
- IDAS: Industrial Data Analysis Service
- Reading data analysis project
PostDoc, University of Oldenburg, Computational Intelligence Lab, Germany
01-2018 - 12-2018
Focus on deep learning methods for time series and image data
Teaching Experience
University of Rostock (since 2025)
- Data Science Course Lectures on Data Science and ML foundations
- Deep Learning for Maritime Vision Applications: Repeated M.Sc. seminar and lectures on applying ML techniques
- Marine Deep Learning: Repeated B.Sc. seminar and lectures on ML and deep learning basics based on application example
University of Copenhagen
- Machine Learning and Imaging Projects (2022-2025): Individual supervision in ML project
- Machine Learning for Science (MLS) (2022-2024): Interdisciplinary course teaching ML basics
- Introduction to Python (2023): Intensive course for non-computer scientists
- Artificial Intelligence (2021): Lectures and exercises on recurrent neural networks
- Large Scale Data Analysis (2020): Lectures and exercises on RNNs and data preparation
- Deep Learning Workshop at CSU (2019): Lecture on RNNs for industry participants
University of Oldenburg
- Artificial Intelligence (2018): Lectures and exercises on evolutionary algorithms and ML
- Data Mining For Maritime Applications (2015): Organized and graded seminar projects
- Computational Intelligence I & II (2014–2018): Grading oral exams as 2nd examiner
- Operating Systems I (2016): Taught tutorials and graded assignments
- Programming Course Java (2010–2011): Taught tutorials and graded assignments
Education
- Dr. rer. nat. in Computer Science (Summa Cum Laude), University of Oldenburg (2014 - 2018)
- M.Sc. in Computer Science, University of Oldenburg (2012 - 2014)
- B.Sc. in Computer Science, University of Oldenburg (2009 - 2012)
Awards & Scholarships
- 2016: Travel Grant, IEEE WCCI
- 2015: Best Presentation, KI 2015
- 2014-2017: Ph.D. Scholarship, SAMS
Committees & Service
- since 08.2025: Journal Editor, Künstliche Intelligenz (KUIN)
- 2022: Workshop Organizer, Pioneer Centre for AI
- 2019: Editorial Manager, Künstliche Intelligenz (KUIN)
- 2019: Program-Committee Member, ICANN