Teaching
- Courses
- Data Programming – Universum College
This course teaches core programming concepts (in Python) with an emphasis on real data manipulation tasks from science, engineering, and business. Goal by the end of the course: Given a data source and a problem description, you can independently write a complete, useful program to solve the problem.
(WiSe2021/22) - Lab “Distributed Big Data Analytics” – (MA-INF 4223) – University of Bonn
The goal is to provide experience and technical skills related to Big data processing tools like Apache Spark, in addition, to make them acquainted with the functional programming style prevalent in concurrent and parallel programming for Big data.
(SoSe2019, WiSe2018/19, SoSe2018, WiSe2017/18, SoSe2017)
- Data Programming – Universum College
- Supervision
- Ardit Meti, 2020; Master Thesis: “An Efficient and Scalable Translational Embedding Model for Dynamic Knowledge Graphs”
(co-supervision with Prof. Dr. Jens Lehmann) - Emetis Niazmand, 2019 - 2020; Master Thesis: “An Efficient Semantic Summary Graph for Querying Large RDF Datasets using SANSA Framework”
(co-supervision with Prof. Dr. Jens Lehmann) - Gresa Halimi (University of Prishtina), 2019; Master Thesis: “A Scalable Semantic PageRank for Ranking Web Search Results”
(co-supervision with Prof. Dr. Lule Ahmedi) - Amrit Kaur, 2019; Master Thesis: “Scalable Entity Resolution”
(minor supervision, co-supervision with Dr. Hajira Jabeen and Prof. Dr. Jens Lehmann) - Haziiev Eskender. 2019; Master Thesis: “Distributed in-Memory SPARQL Processing Engine over Tensor Data”
(minor supervision, co-supervision with Dr. Hajira Jabeen and Prof. Dr. Jens Lehmann) Pratik Kumar Agarwal, 2019; Master Thesis: “Scalable RDF Clustering”
(minor supervision, co-supervision with Dr. Hajira Jabeen and Prof. Dr. Jens Lehmann)- David Ibhaluobe, 2019; Master Thesis: “A Scalable SPARQL Query Engine Over Large-Scale Compressed RDF Data Using SANSA”
(co-supervision with Dr. Damien Graux and Prof. Dr. Jens Lehmann) - Moumen Elteir, 2018 - 2019; Master Thesis: “Efficient real-time quality assessment for large-scale RDF datasets using SANSA“
(co-supervision with Prof. Dr. Jens Lehmann) - Pardeep Naik, 2018 - 2019; Master Thesis: “An efficient recommendation system for RDF partitioners over large-scale RDF datasets”
(co-supervision with Dr. Ioanna Lytra and Prof. Dr. Jens Lehmann) - Mohammad Ghasemi, 2018 - 2019; Master Thesis: “An efficient semantic-based Entity-Resolution over Big RDF data with SANSA framework”
(co-supervision with Prof. Dr. Jens Lehmann) - Abakar Bouba, 2018 - 2019; Master Thesis: “RDF Data Compression Techniques in a Highly Distributed Context”
(co-supervision with Dr. Damien Graux and Prof. Dr. Jens Lehmann) - Gulnar Khalilova, 2018; Master Thesis
(co-supervision with Dr. Anisa Rula and Prof. Dr. Jens Lehmann) - Tina Boroukhian, 2018; Bachelor Thesis: “Distributed RDF Clustering Framework”
(minor supervision, co-supervision with Dr. Hajira Jabeen and Prof. Dr. Jens Lehmann) - Wang Zhe, 2018; Master Thesis: “Efficient In-memory Graph Partitioning Algorithms and Query Engine for RDF Data”
(co-supervision with Dr. Ioanna Lytra and Prof. Dr. Jens Lehmann) - Kunal Jha, 2018; Master Thesis: “Rule Mining on Distributed RDF Data”
(co-supervision with Dr. Hajira Jabeen, Tommaso Soru, Michael Roeder and Prof. Dr. Jens Lehmann) - Rajjat Dadwal, 2018; Master Thesis: “Scalable Numerical Outlier Detection in Knowledge Graphs”
(minor supervision, co-supervision with Dr. Hajira Jabeen and Prof. Dr. Jens Lehmann) - Theresa Nathan, 2017 - 2018; Bachelor Thesis: “Association Rule Mining of Linked Data Using Apache Spark”
(minor supervision, co-supervision with Dr. Hajira Jabeen and Prof. Dr. Jens Lehmann) - Mohamad Denno, 2017 - 2018; Master Thesis: “Scalable deep learning technique for sensitive data exposure detection”
(co-supervision with Dr. Hajira Jabeen and Prof. Dr. Jens Lehmann - Ali Denno, 2017 - 2018; Master Thesis: “Scalable Knowledge Graph Exploration for Sentiment Classification”
(co-supervision with Dr. Hajira Jabeen and Prof. Dr. Jens Lehmann - Imran Khan, 2017 - 2018; Master Thesis: “Efficient and Scalable in-memory Semantic Partitioning for RDF Data”
(co-supervision with Dr. Ioanna Lytra and Prof. Dr. Jens Lehmann - Nayef Roqaya, 2017 - 2018; Master Thesis: “Distributed Data Parsing and Vandalism Detection on Large Knowledge Graphs using Apache Spark and Hadoop Ecosystem”
(co-supervision with Dr. Hajira Jabeen and Prof. Dr. Jens Lehmann - Rohan Asmat, October 2017 - June 2019; Web Development.
- Julius Kaufmann, December 2017 - January 2019; DevOps.
- Adrian Bajraktari, June - September 2018; Web Development.
- Ardit Meti, 2020; Master Thesis: “An Efficient and Scalable Translational Embedding Model for Dynamic Knowledge Graphs”