Christian Hundt, Dr.

Portraitfoto Hundt

Johannes Gutenberg University Mainz
Institute of Computer Science
Staudingerweg 9
55128 Mainz
Room: 03-126

E-Mail:
Phone number: +49 6131 39-23615

 

Research Interests

  • High Performance Computing
  • Gene Set Enrichment Analysis
  • Elastic Alignment of Sequential Data
  • Time Series Data Mining
  • Lie Group-based Quantization Maps in non-relativistic QM
  • Classification and Segmentation of Medical Data
  • Metagenomic Classification
  • Image Processing and Neural Networks

Publications

Time Series Data Mining

  • Christian Hundt, Bertil Schmidt, Elmar Schömer, Herbert Göttler, and Hoang-Vu Dang. GEM:
    An Elastic and Translation-Invariant Similarity Measure with Automatic Trend Adjustment.
    Proceedings of the 29th Annual ACM Symposium on Applied Computing (SAC ’14). ACM,
    New York, NY, USA, pp. 105-112
  • Christian Hundt, Bertil Schmidt, and Elmar Schömer. CUDA-Accelerated Alignment of
    Subsequences in Streamed Time Series Data. 2014 43rd International Conference on Parallel
    Processing, Minneapolis MN, 2014, pp. 10-19.

Bioinformatics

  • Christian Hundt, Andreas Hildebrandt, and Bertil Schmidt. rapidGSEA: Speeding Up Gene
    Set Enrichment Analysis on Multi-core CPUs and CUDA-Enabled GPUs. BMC Bioinformatics
    17 (2016): 394.
  • Jorge González-Domínguez, Christian Hundt, and Bertil Schmidt. parSRA: A Framework for
    the Parallel Execution of Short Read Aligners on Compute Clusters. Journal of Computational
    Science, 2017, ISSN 1877-7503.
  • Daniel Jünger, Christian Hundt, Jorge González-Domínguez, and Bertil Schmidt. Ultra-Fast
    Detection of Higher-Order Epistatic Interactions on GPUs. 4th International Workshop on
    Parallelism in Bioinformatics (PBio 2016), Grenoble, France, August 2016.
  • Daniel Jünger, Christian Hundt, Jorge González-Domínguez, and Bertil Schmidt. Speed
    and Accuracy Improvement of Higher-Order Epistasis Detection on CUDA-Enabled GPUs.
    Cluster Computing-The Journal of Networks Software Tools and Applications, 20(3), 2017,
    pp. 1899-1908. (invited paper)
  • Robin Kobus, Christian Hundt, André Müller, and Bertil Schmidt. Accelerating Metagenomic
    Read Classification on CUDA-Enabled GPUs. BMC Bioinformatics, 18 (2017): 11.
  • André Müller, Christian Hundt, Andreas Hildebrandt, Thomas Hankeln, and Bertil Schmidt.
    MetaCache: Context-Aware Classification of Metagenomic Reads using Minhashing. Bioinformatics,
    Volume 33, Issue 23, 1 December 2017, pp. 3740–3748.

Medical Imaging

  • Christoph Brochhausen, Hinrich B. Winther, Christian Hundt, Volker H. Schmitt, Elmar
    Schömer, and Charles J. Kirkpatrick. A Virtual Microscope for Academic Medical Education:
    the Pate Project. Interact J Med Res 2015, 4(2):e11.
  • Hinrich B. Winther, Christian Hundt, Bertil Schmidt, et al. ν-net: Deep Learning for
    Generalized Biventricular Mass and Function Parameters using Multicenter Cardiac MRI
    Data. Accepted and to be published in the Journal of the American College of Cardiology:
    Cardiovascular Imaging (Impact Factor: 10.189)

High Performance Computing

  • Xiaohui Duan, Kai Xu, Yuandong Chan, Christian Hundt, et al., S-Aligner: Ultrascalable
    Read Mapping on Sunway Taihu Light. 2017 IEEE International Conference on Cluster
    Computing (CLUSTER), Honolulu, HI, 2017, pp. 36-46
  • Daniel Jünger, Christian Hundt, and Bertil Schmidt. WarpDrive: Massively Parallel Hashing
    on Multi-GPU Nodes. Unconditional accept in first round (only 38 out of 461 papers ≈
    8% acceptance rate) and to be published in Proceedings of the International Parallel and
    Distributed Processing Symposium (IPDPS) 2018

Teaching of Parallel Programming

  • Moritz Schlarb, Christian Hundt, and Bertil Schmidt. SAUCE: A Web-Based Automated
    Assessment Tool for Teaching Parallel Programming. Euro-Par 2015 International Workshops,
    Vienna, Austria, August 24-25, Revised Selected Papers, 2015, pp. 54–65.
  • Christian Hundt, Moritz Schlarb, and Bertil Schmidt. SAUCE: A Web Application for Interactive
    Teaching and Learning of Parallel Programming. Journal of Parallel and Distributed
    Computing, Volume 105, 2017, pp. 163–173, ISSN 0743-7315. (invited paper)
  • Bertil Schmidt, Jorge González-Domínguez, Christian Hundt, and Moritz Schlarb. Parallel
    Programming: Concepts and Practice. Textbook at Morgan Kaufmann
    (Elsevier), November 2017, pp. 1–416, ISBN 9780128498903.

Teaching

Head Assistance

  • Mathematics for Computer Scientist
  • Data Structure and Efficient Algorithms
  • Introduction to Programming
  • High Performance Computing
  • Parallel Architectures and Algorithms
  • Programming Practical for Teachers

Under my own supervision

  • Lecture: Parallel Architectures and Algorithms
  • Learn Linux the Hard Way Seminar
  • Programming Course: Visualization with Python