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Dr. Michel Lang

Statistische Methoden in der Genetik und Chemometrie


Michel Lang
Raum 722
0231 755 - 3128
Fakultät Statistik
Technische Universität Dortmund
44221 Dortmund


  • Maschinelles Lernen
  • Große Datenmengen
  • Predictive Modelling
  • Statistical Computing
  • Parallelisierung
  • Hyperparameter-Tuning
  • Black-Box Optimierung
  • Überlebenszeitanalyse
  • Statistische Methoden in der Bioinformatik



  • Michel Lang. checkmate: Fast Argument Checks for Defensive R Programming. The R Journal, vol. 9 no. 1, pages 437-445, 2017.
  • B. Bischl, J. Richter, J. Bossek, D. Horn, J. Thomas and M. Lang. mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions. ArXiv e-prints, March 2017.
  • Michel Lang, Bernd Bischl and Dirk Surmann. batchtools: Tools for R to work on batch systems. The Journal of Open Source Software, vol. 2 no. 10, 2017. [DOI]
  • Helena Kotthaus, Jakob Richter, Andreas Lang, Janek Thomas, Bernd Bischl, Peter Marwedel, Jörg Rahnenführer and Michel Lang. RAMBO: Resource-Aware Model-Based Optimization with Scheduling for Heterogeneous Runtimes and a Comparison with Asynchronous Model-Based Optimization. In Proceedings of the 11th International Conference: Learning and Intelligent Optimization (LION 11) (accepted for publication).. Lecture Notes in Computer Science, Springer, 2017.
  • Andrea Bommert, Jörg Rahnenfürer and Michel Lang. A Multicriteria Approach to Find Predictive and Sparse Models with Stable Feature Selection for High-Dimensional Data. Computational and Mathematical Methods in Medicine, 2017. [DOI]
  • Michel Lang. Efficient R Programming. Journal of Statistical Software, Book Reviews, vol. 80 no. 3, pages 1-4, 2017. [DOI]
  • B. Bischl, G. Casalicchio, M. Feurer, F. Hutter, M. Lang, R. G. Mantovani, J. N. van Rijn and J. Vanschoren. OpenML Benchmarking Suites and the OpenML100. ArXiv e-prints, August 2017.
  • Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren and Bernd Bischl. OpenML: An R package to connect to the machine learning platform OpenML. Computational Statistics, Jun 2017. [DOI]


  • Jakob Richter, Helena Kotthaus, Bernd Bischl, Peter Marwedel, Jörg Rahnenführer and Michel Lang. Faster Model-Based Optimization Through Resource-Aware Scheduling Strategies. In Learning and Intelligent Optimization, pages 267-273. Springer, Cham, May 2016. [DOI]
  • Bernd Bischl, Michel Lang, Lars Kotthoff, Julia Schiffner, Jakob Richter, Erich Studerus, Giuseppe Casalicchio and Zachary M. Jones. Mlr: Machine Learning in R. Journal of Machine Learning Research, vol. 17 no. 170, pages 1-5, 2016.


  • Michel Lang. Automatische Modellselektion in der Überlebenszeitanalyse. Dissertation, TU Dortmund, Dortmund, 2015.
  • Bernd Bischl, Michel Lang, Olaf Mersmann, Jörg Rahnenführer and Claus Weihs. BatchJobs and BatchExperiments: Abstraction Mechanisms for Using R in Batch Environments. Journal of Statistical Software, vol. 64 no. 11, pages 1-235, 2015.


  • S. Lee, J. Rahnenführer, M. Lang, K. De Preter, P. Mestdagh, J. Koster, R. Versteeg, R. L. Stallings, L. Varesio, S. Asgharzadeh, J. H. Schulte, K. Fielitz, M. Schwermer, K. Morik and A. Schramm. Robust selection of cancer survival signatures from high-throughput genomic data using two-fold subsampling. PLoS ONE, vol. 9 no. 10, page e108818, 2014.
  • Helena Kotthaus, Ingo Korb, Michel Lang, Bernd Bischl, Jörg Rahnenführer and Peter Marwedel. Runtime and memory consumption analyses for machine learning R programs. Journal of Statistical Computation and Simulation, vol. 85 no. 1, pages 14-29, June 2014. [DOI]
  • Michel Lang, Helena Kotthaus, Peter Marwedel, Claus Weihs, Jörg Rahnenführer and Bernd Bischl. Automatic model selection for high-dimensional survival analysis. Journal of Statistical Computation and Simulation, vol. 85 no. 1, pages 62-76, June 2014. [DOI]


  • Bernd Bischl, Michel Lang, Olaf Mersmann, Jörg Rahnenführer and Claus Weihs. Computing on high performance clusters with R: Packages BatchJobs and BatchExperiments. Technical Report 1/2012, TU Dortmund, Department of Statistics, 2012.


  • Kai Kammers, Michel Lang, Jan G Hengstler, Marcus Schmidt and Jörg Rahnenführer. Survival models with preclustered gene groups as covariates.. BMC Bioinformatics, vol. 12 no. 478, January 2011. [DOI]


GitHub Profile


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