Mark Blacher

Mark Blacher
Professorship of Theoretical Computer Science II
Mark Blacher
Room 3312
Ernst-Abbe-Platz 1-2
07743 Jena


  • J. Klaus, M. Blacher, J. Giesen. Compiling Tensor Expressions into Einsum.  Proceedings of the 23d International Conference on Computational Science (ICCS), 2023
  • M. Blacher, J. Giesen, J. Klaus, C. Staudt, S. Laue, and V. Leis. Efficient and Portable Einstein Summation in SQL. Proceedings of the 49th ACM SIGMOD Conference on Management of Data (SIGMOD), 2023 (PDFpdf, 765 kb · de)
  • J. Klaus, M. Blacher, A. Goral, P. Lucas, J. Giesen. A visual analytics workflow for probabilistic modeling. Visual Informatics, Vol. 7, 2023 (PDFExternal link)
  • J. Klaus, M. Blacher, J. Giesen, P. Rump and K. Wiedom. Compiling Linear Algebra Expressions into Efficient Code. Proceedings of the 22nd International Conference on Computational Science (ICCS), (2022)
  • S. Laue, M. Blacher and J. Giesen. Optimization for Classical Machine Learning Problems on the GPU. Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI), (2022) accepted
  • M. Blacher, J. Giesen, S. Laue, J. Klaus, and V. Leis. Machine Learning, Linear Algebra, and More: Is SQL All You Need?External link Proceedings of the Conference on Innovative Data Systems Research (CIDR), (2022) accepted
  • M. Blacher, J. Giesen and L. Kühne. Fast and Robust Vectorized In-Place Sorting of Primitive TypesExternal linkProceedings of the 19th Symposium on Experimental and Efficient Algorithms (SEA), (2021) 3:1-3:16
  • Mark Blacher, Joachim Giesen, Sören Laue, Julien Klaus, Matthias Mitterreiter
    Fast Entity Resolution With Mock Labels and Sorted Integer Sets. External linkProceedings of the 2nd International Workshop on Challenges and Experiences from Data Integration to Knowledge Graphs co-located with 46th International Conference on Very Large Data Bases, (2020)

Supervised Student Theses

  • Design and Implementation of Vectorized Pseudorandom Number Generators and their Application to Simulations of Photon Propagation (2019)
  • Design and Implementation of Artifact Removal Approaches for Color Quantized Images (2020)
  • Design and Implementation of a vectorized and parallelized Quicksort (2021)
  • Implementation of a vectorized Quicksort using AVX-512 intrinsics (2021)
  • Automatic Generation of Efficient Linear Algebra Expressions (2021)


  • Winner of the ACM SIGMOD Programming Contest (2019)
  • SPP Algorithms for BIG DATA: Young Talent Award (2019)
  • Exam Award of the President of the Friedrich Schiller University Jena (2019)
  • Winner of the ACM SIGMOD Programming Contest (2020)