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            • Theses Supervision | Dr. Jens Lechtenbörger
 
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Dr. Jens Lechtenbörger
Faculty

Chair of Machine Learning and Data Engineering (Prof. Gieseke)

Leonardo Campus 3
48149 Münster


Room: 229

Phone: +49 251 83-38158
jens.lechtenboerger@wi.uni-muenster.de

Consultation hours:
Upon request via e-mail.


External profiles:
ORCID

ShortURL: ERC.IS ShortURL erc.is/p/jl

  • About
  • Publications
  • Projects
  • Awards
  • Courses
  • Theses Supervision
  • Supervised Theses

    • Design and implementation of a privacy-preserving learning analytics module for reveal.js presentations (Master's thesis IS, 2025)
    • Evaluating the Integration of Synthetic Data for Computer Vision Projects in the Utilities Sector (Master's thesis IS, 2025)
    • Model-Based Testing for Business Logic Vulnerabilities (Master's thesis IS, 2025)
    • Leveraging Self-Supervised Learning for Green Feed Contamination Classification in Forage Harvesters (Master's thesis IS, 2024)
    • Design and Implementation of a Recipe Recommendation System (Bachelor's thesis IS, 2024)
    • Small-Scale Monitoring of Networked Systems: A Case Study on an Electronic Kiosk (Bachelor's thesis IS, 2024)
    • Gap Analysis and Data Mesh Implementation Concept for an Innovative Data Management Automation Framework (Master's thesis IS, 2024)
    • Evaluation of a semi-supervised learning approach using deep learning for labeling an image dataset for multi-class classification in the quality inspection of a manufacturing company (Bachelor's thesis IS, 2024)
    • Prototypical development and evaluation of an interface concept for the provision of dispositive data as part of a data and analytics rebuild (Bachelor's thesis IS, 2023)
    • Analyzing the Effectiveness of the Data Vault 2.0 Architecture in Property Insurance: A Case Study at LVM (Bachelor's thesis IS, 2023)
    • Knowledge graph generation for web-based educational resources (Master's thesis IS, 2023)
    • Data Preparation for a Web-Based Learning Analytics Platform (Bachelor's thesis IS, 2023)
    • Social Presence in Reveal.js Online Learning Environments (Master's thesis IS, 2023)
    • Collecting personal learner information in digital education: From tedious questionnaire to entertaining chatbot experience (Master's thesis IS, 2022)
    • Web tracking and its application for Learning Analytics: A case study with reveal.js (Master's thesis IS, 2022)
    • Customer Behavior Predictions for Online Travel Agencies: A Practical Implementation (Master's thesis IS, 2022)
    • Data provenance for a semantically-structured representation of license information for open educational resources (Bachelor's thesis IS, 2022)
    • Extension of the classical business intelligence architecture for the handling of big data (Bachelor's thesis IS, 2021)
    • Taxonomy for governments and state actors to counter online radicalisation (Bachelor's thesis IS, 2021)
    • Adaptive Reveal.js Presentations with Personalized Learning Paths (Master's thesis IS, 2021)
    • Chat bots as digital learning assistants: Overview and prototypical implementation (Bachelor's thesis IS, 2020)
    • Pseudonymous tracking of reveal.js presentations for learning analytics (Bachelor's thesis IS, 2020)
    • Standardized Integration Process of Sales Data between B2B Enterprises and Data Analytics Service Providers: Concept and Prototypical Implementation (Master's thesis IS, 2020)
    • Test methods for web applications using the example of reveal.js (Bachelor's thesis IS, 2020)
    • Digital Learning Journey of the Future - Structure and Success Factors of Learning Management Systems (Bachelor's thesis IS, 2019)
    • Challenges of Blockchain Design (Master's thesis IS, 2018)
    • Digitalization of higher education teaching with particular focus on the University of Muenster's School of Business and Economics (Bachelor's thesis IS, 2018)
    • Recommendations for the use of OER repositories at universities (Bachelor's thesis IS, 2018)
    • State of the art of penetration testing (Bachelor's thesis IS, 2017)
    • Cloud-based BI Solutions (Bachelor's thesis IS, 2016)
    • Synchronizing encrypted data on Android (Bachelor's thesis IS, 2015)
    • Design and implementation of an extensible data profiling tool (Master's thesis IS, 2015)
    • Gamification for university courses (Bachelor's thesis IS, 2015)
    • Offline Localization Techniques for Smartphones (Bachelor's thesis IS, 2015)
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Contact

Data Science: Machine Learning and Data Engineering
Prof. Dr. Fabian Gieseke

Leonardo-Campus 3
48149 Münster
Deutschland

Tel.: +49 251 83-38150
Fax: +49 251 83-38159
sek-dasc@wi.uni-muenster.de

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