• Machine Learning Systems
• Interoperability in Collaborative Environments
• Distributed Machine Learning
• Model management

• Addressing Data Management Challenges for Interoperable Data Science @DATAI '24 (co-located with VLDB)
  Ilin Tolovski, Tilmann Rabl
  > Paper
• RMG Sort: Radix-Partitioning-Based Multi-GPU Sorting @BTW '23
  Ivan Ilic, Ilin Tolovski, Tilmann Rabl
  > Paper
• Efficiently Managing Deep Learning Models in a Distributed Environment @EDBT '22
  Nils Strassenburg, Ilin Tolovski, Tilmann Rabl
  > Paper
• Evaluating Multi-GPU Sorting with Modern Interconnects @SIGMOD '22
  Tobias Maltenberger, Ivan Ilic, Ilin Tolovski, Tilmann Rabl
  > Paper
• DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines
  @ CIDR '22 
  Pattrick Damme, Marius Birkenbach, Constantinos Bitsakos, Matthias Boehm, Phillipe Bonnet, Florina Ciorba, Mark Dokter, Pawl Dowgiallo, Ahmed Eleliemy, Christian Faerber, Georgios Goumas, Dirk Habich, Niclas Hedam, Marlies Hofer, Wenjun Huang, Kevin Innerebner, Vasileios Karakostas, Roman Kern, Tomaž Kosar, Alexander Krause, Daniel Krems, Andreas Laber, Wolfgang Lehner, Eric Mier, Tilmann Rabl, Piotr Ratuszniak, Pedro Silva, Nikolai Skupin, Andreas Starzacher, Benjamin Steinwender, Ilin Tolovski, Pinar Tözün, Wojciech Ulatowski, Yuanyuan Wang, Izajasz Wrosz, Aleš Zamuda, Ce Zhang, Xiao Xiang Zhu
  > Paper
• A Survey of Big Data, High Performance Computing, and Machine Learning Benchmarks
  @ TPCTC '21 (co-located with VLDB)
  Nina Ihde, Paula Marten, Ahmed Eleliemy, Gabrielle Poerwawinata, Pedro Silva, Ilin Tolovski, Florina M. Ciorba, Tilmann Rabl
  > Paper

Lectures:

• Big Data Lab (Master, Winter 2023/24)
• Big Data Systems (Master, Winter 2020/21, 2021/22)
• Database Systems I (Bachelor, Summer 2020)
• Hardware-conscious Data Processing (Master, Summer 2022, 2023, 2024)

Projects/Seminars:

• Machine Learning Systems (Master, Winter 2023/24)
• Interoperability in Data Processing Pipelines (Master, Winter 2022/23)
• Data Management in ML Systems (Master, Winter 2021/22)
• GPU-Accelerated Data Processing (Master, Winter 2020/21)
• Data Processing on Modern Hardware (Master, Summer 2020)

Master & Bachelor Projects:

• Tracking Carbon: Multi-Tier Analysis of Compute Job Emissions in Datacenters (Bachelor Project, 2023/24)
• Model Lifecycle Analysis Platform (Master Project, Summer 2022)
• End-to-end ML System Benchmarking (Bachelor Project, 2020/21)

Thesis Supervision: 

If you are interested in writing your thesis with me, have a look at the open theses page for some ideas and guidelines. If you have an interesting idea that you want to work on, feel free to drop me a line.

Completed Theses:

• Squirrel: A Carbon-Aware HPC Scheduler utilizing Spatiotemporal Workload Shifting, Luca Springer, Master Thesis, 2024
• Efficiently Joining Large Relations on Multi-GPU Systems with Modern Interconnects, Tobias Maltenberger, Master Thesis, 2024
• RMG Sort: Radix-Partitioning-Based Multi-GPU Sort, Ivan Ilic, Master Thesis, 2022
• Model Management in Distributed Environments, Nils Straßenburg, Master Thesis, 2021
• Benchmarking Distributed Machine Learning Systems, Willi Rieck, Bachelor Thesis, 2021
• Benchmarking Containerized Machine Learning Pipelines, Jost Morgenstern, Bachelor Thesis, 2021
• Real-Time Benchmarking, Jonas Schulze, Bachelor Thesis, 2021
• UI Designs for Benchmarking Systems, Christian Jacob, Bachelor Thesis, 2021