I am currently pursuing my Ph.D. in Computer Science at the Technical University of Munich (TUM) under the supervision of Prof. Dr. Hans-Arno Jacobsen.
My research interests focus on improving the performance of large-scale Distributed Graph Neural Network Systems and Distributed Graph Processing Systems through Graph Partitioning and Graph Reordering.
Education
- Ph.D. in Computer Science, Technical University of Munich (TUM), Since August 2020
- M.Sc., Technical University of Munich (TUM), Completed in June 2020
Scholarships
- Max Weber Program of the state of Bavaria: “The Max Weber Program supports gifted and talented students at Bavarian tertiary education institutions.”
- Scholarship from the German National Academic Foundation: “The German Academic Scholarship Foundation is Germany’s largest, oldest and most prestigious scholarship foundation.”
Publications
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Can Graph Reordering Speed Up Graph Neural Network Training? An
Experimental Study.
Nikolai Merkel, Pierre Toussing, Ruben Mayer, and Hans-Arno Jacobsen.
In Proceedings of the 51st International Conference on Very Large Data Bases (VLDB '25), September 1-5, London, United Kingdom. Accepted. [Paper]
- An Experimental Comparison of Partitioning Strategies for Distributed Graph Neural Network Training.
Nikolai Merkel, Daniel Stoll, Ruben Mayer, and Hans-Arno Jacobsen.
In Proceedings of the 28th International Conference on Extending Database Technology (EDBT '25), March 25-28, Barcelona, Spain. Accepted. [Paper]
- Partitioner Selection with EASE to Optimize Distributed Graph Processing.
Nikolai Merkel, Ruben Mayer, Tawkir Ahmed Fakir, and Hans-Arno Jacobsen.
In Proceedings of the 2023 IEEE 39th International Conference on Data Engineering (ICDE ’23), April 3-7, 2023, Anaheim, California, USA. Accepted. [Paper]
Teaching
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Advanced Master Seminar: Large-scale Graph Processing and Graph Partitioning
- Winter Semester 2024/25
- Summer Semester 2024
- Winter Semester 2023/24
- Summer Semester 2023
- Winter Semester 2022/23
- Summer Semester 2022
- Winter Semester 2021/22
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Exercises for Operating Systems and Hardware-oriented Programming