Mark Blacher

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


  • 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) accpeted
  • 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? 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 TypesProceedings 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. Proceedings 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)