Sven Ligensa

PhD Researcher @ MLDE group at University of Münster

Working on the application of Transformers and explainability to the field of medicine.

Papers & Projects

Pixel-Level Transformers in Remote Sensing: A Canopy Height Case Study

SIGSPATIAL '26

Efficient Vision Attention Mechanisms for Dense Prediction

Master Thesis

Combining Deep Feature Extraction with Locality-Sensitive Hashing for Reverse Image Search

Bachelor Thesis

Education

PhD in Deep Learning

University of Münster

Advisor: Prof. Dr. Fabian Gieseke · Machine Learning and Data Engineering Group

MLSS Melbourne 2026

Machine Learning Summer School, organized by Maincode

MSc in Information Systems Grade: 1.0 (GPA 4.0/4.0)

University of Münster

Specialization in Data Science (ML, DL, Big Data, Data Management) and Computer Science

Semester Abroad, Erasmus+

Universidad Politécnica de Madrid

BSc in Information Systems Grade: 1.1 (GPA 3.8/4.0)

University of Münster

Awards & Scholarships

Award for Best Master's Degree (Winter Term 2025/26)

University of Münster

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Deutschlandstipendium Scholarship

University of Münster

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Award for Best Thesis in Applied Computer Science (2023)

University of Münster

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Award for Best Bachelor's Degree (Winter Term 2022/23)

University of Münster

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Work

Research Associate

University of Münster · Machine Learning and Data Engineering Group

Conducting research on Transformers and Explainable AI.

Student Research Assistant

University of Münster · MLDE Group

Co-authored and proofread papers, implemented models, created teaching materials.

Data Scientist Intern

CLAAS E-Systems GmbH

  • Developed a pipeline combining geospatial data with internal machine data.
  • Trained regression models on machine data using PySpark to reduce sensor costs.
  • Contributed a classification model and dataset to the internal AI toolkit.

Teaching @ University of Münster

Mining Massive Datasets

Lecture Supportive

AIlaborate

Project Seminar Supportive

Deep Learning

Lecture Supportive

GeoAI Platforms

Project Seminar Supportive