Abschlussarbeiten, die im Fachgebiet DBS betreut werden, bieten Studierenden anspruchsvolle Forschungsprobleme zur Bearbeitung und befähigen sie zur Zusammenarbeit mit nationalen und internationalen Partnern an realen, wissenschaftlichen und wirtschaftsrelevanten Themen. Abschlussarbeiten werden aufgrund der internationalen Ausrichtung des Fachgebietes häufig in Englisch erstellt, können jedoch auch in deutscher Sprache verfasst werden.

Typische Voraussetzungen sind:

• Hervorragende Programmierkenntnisse in eine Programmiersprache
• Erweiterte Kenntnisse in Datenbanksystemen, wie etwa PostgreSQL, IBM DB2 oder Oracle bzw. Big Data Analytics Systemen wie Hadoop, Flink, Spark

If you are interested in doing your thesis with us, read the following instructions carefully: Thesis Process. 

Open Thesis

1- Predict research trends in data science based on arXiv repository [M.Sc.]

2- Ordering datasets for Efficient or Effective Error Detection [M.S.c]

3- Large Language Model-Driven Data Discovery [MSc]

Ongoing Thesis

• Self-supervised Data Cleaning in Data Lakes (M.Sc.)
  • Sebastian Eggers
• Indexing Large Vectors (B.Sc.)
  • Carl Piepgras
• Quality-Driven Union Table Search (M.Sc.)
  • Mehdi Alijani
• Maintenance of large inverted indexes (B.Sc.)
  • Ede Becker
• Bias analysis in large ML training datasets (B.Sc.)
  • Manish Bhatta Kapadi
• Large Scale ML Data Analysis (B.Sc.)
  • Ghareeb Jawish
• Near-Duplicate Table Detection (B.Sc.)
  • Lucas Kiesel
• Will pre-indexing improve deep code search? (B.Sc.)
  • Slim Bougacha
• A unified data representation for few-shot learning (M.Sc.)
  • Ilyes Farhat
• Memory Usage Optimization in Baran
  • Louay Hamdi

Finished Thesis

2023

• Will Index-Based Pre-selection Enhance Deep Code Search Efficiency while Preserving Effectiveness? (B.Sc.)
  • André Warnecke
• Maintenance of large inverted indexes (B.Sc.)
  • Nils Martel
• Maintenance of large inverted indexes (B.Sc.)
  • Firas Frikha
• Comparison of Coherent Grouping Algorithms for Writing Style Suggestion (B.Sc.)
  • Jan Paßlack
• Investigate improving deep code search using information retrieval techniques (B.Sc.)
  • Emad Al-Quhaim

2022

• Column Splitter with Record-Matching (B.Sc.)
  • Trong Hoa Nguyen
• Improving Baran using Embeddings (B.Sc.)
  • Quang Minh Nguyen
• Extracting unbiased text from large text corpora (M.Sc.)
  • Christoph Becker   
• Effectively Sampling Validation Sets (B.Sc.)
  • Mohamed Mahdi Kanoun
• ML Validation Set Mining (B.Sc.)
  • Johannes Waldeck
• Validation Set Selection in Machine Learning (B.Sc.)
  • Achraf Bahloul   
• Detecting Duplicate Tables using Xash (B.Sc.)
  • Maximilian Koch
• Improving Primary Key Detection with Machine Learning (B.Sc.)
  • Janek Prange
• Investigating and improving variable names in data science projects with data mining (M.Sc.)
  • Huu Kim Nguyen   
• Deklarative sukzessive Halbierung (M.Sc.)
  • Ramzi Mezlini
• Performance Benchmarking of Database MAnagement Systems (B.Sc.)
  • Erik Schriefer
• Improving Label Propagation in the Data Cleaning System Raha (B.Sc.)
  • Maximilian Siebenthaler
• Declarative successive halving (M.Sc.)
  • Pinliang Li
• Embedding Data Transformations in AutoML (B.Sc.)
  • Henrik Tipp
• Opinion mining in social media data based on neural networks to predict bitcoin prices (B.Sc.)
  • Marc Speckmann
• Analysing the Influence of social media Influencers on the Bitcoin Price (B.Sc.)
  • Omar Allouni
• Analyzing the relation between social media and Bitcoin’s price variation (B.Sc.)
  • Ahmed Malek Ghanmi
• From mining Naming Conventions in Data Science Projects to suggesting Variable Names (M.Sc.)
  • Philip Ossenkopp
• Scalable Error Detection (B.Sc.)
  • Faical Aridal
• Feature Analysis for Agglomerative Clustering (B.Sc.)
  • Malte Fabian Kuhlmann
• Detecting table headers in heterogeneous tables (B. Sc.)
  • Daniel Ritter

2021

• Instrumentierung von Datenreinigung mit AutoML (B.Sc.)
  • Yazan Alkhatib
• Mining social media to discover the factors that affect bitcoin price (B.Sc.)
  • Jonathan Friebe
• Multi-attribute join search with map-reduce (B.Sc.)
  • Justin Zheng
• Efficient join discovery from large data lakes (B.Sc.)
  • Akram Chorfi
• Multi-attribute join search with map-reduce (B.Sc.)
  • Meike Liedtke
• Interleaving Data Cleaning and AutoML (B.Sc.)
  • Jingwen Ye