Different institutions use different supervision systems. In the list below, I consider myself the supervisor of a student if I had a formal role in the supervision and had supervision meetings with the student. For most works were I was the main supervisor I was either informally or formally grading the work.

Master Thesis works I supervised (some titles shortened for brevity)

• Zhang Jinyang [IDEA grant recipient, with ETH Zürich], Modeling for Street Level Crime Prediction, Media Informatics, RWTH Aachen, Sep 2022, Joint supervision with Cristina Kadar Raquel Rosés Brüngger
• Tiddo Loos, Scaling Relational Graph Convolutional Network Training with Graph Summaries and Entity Embedding Transfer, Artificial Intelligence, VU Amsterdam, Aug 2022
• Nicole Van de Weijer, Combining Images and Tabular Data Using Deep Learning for Classification Tasks, Artificial Intelligence, VU Amsterdam, Aug 2022, Daily supervision by Taewoon Kim. Result of an internship at Clappform (supervisor Jeroen Schoonderbeek)
• Meena Alfons, Multi-dimensional Positional Self-Attention With Differentiable Span, Artificial Intelligence, VU Amsterdam, Aug 2022, Daily supervision by David Romero
• Maximiliane Ekert, Catch Me If You Can: Graph Neural Networks to detect fraudulent nodes to counter money laundering, Artificial Intelligence, VU Amsterdam, Aug 2022, Result of an internship at Deloitte, supervised by Evert Haasdijk, with support from TMNL
• Max Zwager, Approximate Query Answering using Answer Space Discretization, Artificial Intelligence, VU Amsterdam, Aug 2022
• Yu Anlan, Negative Sampling for Knowledge Graph Embedding Using Rule-Based Reasoning, Artificial Intelligence, VU Amsterdam, Dec 2021
• Bob Mes, An approach to map textual questions to a response out of a predefined response set., Business Analytics, VU Amsterdam, Aug 2021
• Huishi Qui, Enhancing Question Answering with a Free-text Knowledge Graph, Artificial Intelligence, VU Amsterdam, Aug 2021
• Enis Zejnilovic, Batch Recommender for Fast Ontology Prototyping, Computer Science, RWTH, Aug 2021
• Tessa Helmer, Semi-supervised Invoice Information Extraction, Business Analytics, VU Amsterdam, Jul 2021, This thesis was done during an internship at SoliTrust
• Reven Passial, Creating a patient embedding for machine learning purposes in healthcare, Business Analytics, VU Amsterdam, Nov 2020, Based on an internship at Chipsoft
• Suchanda Bhattacharyya, Imputation in Graphs Using Machine Learning, Sofware Systems Engineering, RWTH, Jul 2020, Joint supervision with Md. Rezaul Karim
• Mian, Isfandyar, Combining Vehicle Routing Optimization and Container Loading Optimization, Web Intelligence and Service Engineering (WISE), JYU, Mar 2020
• Frankie Robertson, Word Sense Disambiguation for Finnish (language learning), Web Intelligence and Service Engineering (WISE), JYU, Mar 2020
• Abhijeet Das, Feature Clustering and Visualization of High Dimensional Data using Clique Cover Theory, Media Informatics, RWTH, Oct 2019, Joint supervision with Arnacb Chakrabarti and Christoph Quix. A further development of this work was published in the ADBIS 2021 conference
• Michael Ellers, Privacy Attack on Social Networks Using Network Embeddings, Computer Science, RWTH Aachen, Jul 2019, Joint supervision with Florian Lemmerich and Markus Strohmaier
• Jiao Jiao, Deep Learning-based Knee Osteoarthritis Diagnosis from Radiographs and Magnetic Resonance Images, Media Informatics, RWTH Aachen, Jun 2019, Jointly supervised with Oya Beyan and MD. Rezaul Karim. This work got extended into a journal paper available from IEEE access
• Iraklis Dimitriadis, Data Dependence and Indecisiveness for Locality-Sensitive Hashing, Computer Science, RWTH Aachen, Feb 2019
• Touhidur Rahman, Modeling autonomous sensory agents in ROS, Computer Science, RWTH Aachen, Nov 2018, Main supervision Ahmed Hallawa. A much further developed work based on this thesis was published in the Taylor and Francis journal on Materials and Manufacturing Processes
• Leandro Eichenberger, Secure Evaluation of Knowledge Graph Merging Gain, Computer Science, RWTH Aachen, Nov 2018, This thesis got extended into a paper available from arXiv
• Jasim Waheed Ansari, Semantic Data Profiling in Data Lake, Computer Science, RWTH Aachen, Feb 2018, main supervision Oya Beyan
• Georg Groß, Go with the Flow - Exponential Decaying Reservoir Sampling of Evolving Data Streams, Computer Science, RWTH Aachen, Dec 2017
• Andrei Ionita, Extending Estimation of Parking Occupancy to Untracked City Areas using City Background Information, Computer Science, RWTH Aachen, Dec 2017
• Phesto Mwakyusa, Semantic Annotation for Big Data, Mobile Technology and Business (MoTeBu), JYU, Nov 2017
• Gesche Gierse, The Pragmatics and Logic of Knowledge Representation with Prototypes, Computer Science, RWTH Aachen, Oct 2017, main supervision Stefan Decker
• Bushra Zafar, Using Distributional Semantics For Automatic Taxonomy Induction, Computer Software Engineering (NUST, Pakistan), JYU, Nov 2016, co-supervision with Dr.Usman Qamar, NUST Pakistan
• Lauri Satokangas & Olli Heimonen, Technology Selection for Off-line Web Applications, Mathematical Information Technology, JYU, Nov 2015, Original Finnish title: Teknologian valinta yhteydettömässä tilassa toimivan web-sovelluksen kehittämiseen
• Jiawen Chen, Smart Semantic Multi-channel Communication, Mobile Technology and Business (MoTeBu), JYU, Feb 2015

Bachelor Thesis works I supervised (some titles shortened for brevity)

• Tommy Lohn, Evaluating a Proposed Link Interestingness Measure Using Oversampling of Triples in Knowledge Graphs, Artificial Intelligence, VU Amsterdam, Aug 2022, Daily supervision by Dimitris Alivanistos
• Renske Diependaal, Finding a good set of anchors for NodePiece, Artificial Intelligence, VU Amsterdam, Aug 2022
• Fredrik Skjelvik, Complex Query Answering in the Biomedical Domain, Artificial Intelligence, VU Amsterdam, Aug 2022, Daily supervisor Daniel Daza
• Razvan Gabriel Olaru, Selective Reduction of Dimensions for NodePiece Anchors, Computer Science, VU Amsterdam, Aug 2022
• Jord Beek, A Research Proposal on Improving Convolutional Neural Network Predictions of Deforestation Using Geographic Information Systems Data, Artificial Intelligence, VU Amsterdam, Aug 2022
• Simone Colombo, Creating differentiable graph metrics to improve link prediction, Computer Science, VU Amsterdam, Mar 2022, This work was also published as a paper at the AAAI Spring Symposium: MAKE
• Marta Jansone, Deployment and Evaluation of a New Recommender System for Wikidata, Computer Science, VU Amsterdam, Aug 2021
• Ken Mikovíny, MPQE Training on Entity Types, Computer Science, VU Amsterdam, Aug 2021
• Alessandro Generale, Scaling RGCN Training through Graph Summarization, Computer Science, VU Amsterdam, Aug 2021
• Karim Anwar, Benefits of data scalability and transfer learning for relational graph data, Computer Science, VU Amsterdam, Jul 2021
• Ruud van Bakel, Box R-GCN: Structured Query Answering Using Box Embeddings For Entities And Queries, Artificial Intelligence, VU Amsterdam, Aug 2020, This work was also presented as a paper at the GKR2020 workshop link
• Teodor Aleksiev, Answering approximated graph queries, embedding the queries and entities as boxes, Computer Science, VU Amsterdam, Aug 2020, This work was also presented as a paper at the GKR2020 workshop link
• Minh Hai Nguyen, Data imputation with deep learning and a comparison with statistical techniques, Computer Science, VU Amsterdam, Aug 2020
• Hristo Petkov, Building on (Relational) Graph Convolutional Networks with Markov Chains, Computer Science, VU Amsterdam, Aug 2020
• Ayoub Abdelouarit, Fadi Meggouh, Bente Meijer, Maud Smulders, Lucien Tuijp, Business case Nofalab, group 2, Business Analytics, VU Amsterdam, Jul 2020
• Bart Silven, Pieter Steur, Dave de Moel, Sebastiaan Nijman, Business case Nofalab, group 1, Business Analytics, VU Amsterdam, Jul 2020
• Philipp Lützenkirchen, Evaluation of Hierarchical Clustering Algorithms, Computer Science, FH Aachen, Sep 2019, Joint supervison with Martin Reißel [FH Aachen]
• Christopher Wewer, Dynamic Embeddings of Evolving Knowledge Graphs, Computer Science, RWTH, Aug 2019, Joint supervision with Florian Lemmerich, a restructured version of the work can be found on arxiv
• Sophie Hallstedt, Machine Learning for Anonymization of Unstructured Text, Computer Science, RWTH Aachen, Aug 2019
• Abdulrahman Altaba, Accelerating KGlove Graph Embedding, Computer Science, RWTH Aachen, Feb 2019
• Felix Ingenerf, Concept embeddings for Wikipedia across language editions, Computer Science, RWTH Aachen, Jan 2019, main supervision Florian Lemmerich, graded by Markus Strohmaier and Stefan Decker
• Jérôme Lenßen, Including Attributes in a Graph Embedding, Computer Science, RWTH Aachen, Oct 2018
• Dominik Hüser, Prototypes on IPFS: A Realization of globally distributed reusable Knowledge, Computer Science, RWTH Aachen, Oct 2017, An extension of this work was published as a paper in the ICDCS 2017 conference.

Examiner / second reader

Besides the thesis works above, I was appointed as the examiner for the following thesis works, where I was not involved in the supervision process.

• Atilla Erdodi, Reducing the memory footprint of Knowledge Graph Embeddings, Computer Science, VU Amsterdam, Aug 2020
• Paulo Alting von Gesau, Evaluating the Robustness of Question-Answering Models to Paraphrases, Computer Science, VU Amsterdam, Aug 2020
• Ward Pennink, Automatically Fitting Probability Distributions to Data Samples Using a Convolutional Neural Network, Information Sciences, VU Amsterdam, Aug 2020, Supervision by Albert Meroño Peñuela
• Ayuub Hussein, Convolutional Neural Networks for Probability Distribution Classification -- An QQ plot Based Application, Information Sciences, VU Amsterdam, Aug 2020, Supervision by Albert Meroño Peñuela
• Xinran Yang, Creative Storytelling with Knowledge Graphs, Information Sciences, VU Amsterdam, Jul 2020, Supervision by Ilaria Tiddi
• Mathias Parisot, Property Inference Attack on Neural Networks: Influence of the Architecture and Implications of the GDPR, Computer Science, VU Amsterdam, Jul 2020, Supervision by Dayana Spagnuelo
• Selma Muhammad, Auditing Algorithmic Fairness with Unsupervised Bias Discovery, Artificial Intelligence, VU Amsterdam, Jan 1970, Supervision by Emma Beauxis-Aussalet, with an internship at the City of Amsterdam
• Marcel Schuchmann, Designing a cloud architecture for an application with many users, Web Intelligence and Service Engineering (WISE), JYU, May 2018
• Pekka Suopellonmäki, GUI Personalization Framework using Semantic User Profile, Web Intelligence and Service Engineering (WISE), JYU, Dec 2017