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HK.png Email: helena.kotthaus At sign tu-dortmund.de
Phone: 0231/755-6325
Fax: 0231/755-5105
Room-No.: OH12 R4.021

About

Helena Kotthaus is a senior researcher at the Competence Center for Machine Learning Rhine-Ruhr (ML2R) in Dortmund, Germany. Within ML2R she is responsible for the transfer between research, business, and industrial projects. Her research interests focus on achieving trustworthiness and resource-efficiency in machine learning algorithms. By evaluating typical pitfalls in data science processes she aims at increasing explainability and trustworthiness of machine learning pipelines. Helena Kotthaus received her Ph.D. from TU Dortmund University for her work on “Methods for Efficient Resource Utilization in Statistical Machine Learning Algorithms” in 2018. By applying methods from the research field of embedded systems to machine learning algorithms, she was able to reduce memory and runtime consumption, particularly for computationally intensive black-box optimizations. She worked as a staff member at TU Dortmund University’s Embedded Systems Group and the DFG Collaborative Research Center SFB 876 on “Providing Information by Resource-Constrained Data Analysis”. After visiting Oracle Labs, Belmont in 2012, she received a grant from Oracle to coordinate a project on performance comparison methods for the GNU R language. Helena contributed to different research projects, especially on parallelization strategies that enable machine learning algorithms to run efficiently on mobile devices.

Projects

Publications

Haritz/etal/2021a Haritz, Pierre and Pfahler, Lukas and Liebig, Thomas and Kotthaus, Helena. Self-Supervised Source Code Annotation from Related Research Papers. In Proceedings of the PhD Forum of the 21st IEEE International Conference on Data Mining, pages 1083-1084, 2021.
Kotthaus/etal/2019a Tözün, Pinar and Kotthaus, Helena. Scheduling Data-Intensive Tasks on Heterogeneous Many Cores. In IEEE Data Engineering Bulletin, Vol. 42, No. 1, pages 61-72, 2019. Arrow Symbol
Kotthaus/etal/2019b Kotthaus, Helena and Schönberger, Lea and Lang, Andreas and Chen, Jian-Jia and Marwedel, Peter. Can Flexible Multi-Core Scheduling Help to Execute Machine Learning Algorithms Resource-Efficiently?. In 22nd International Workshop on Software and Compilers for Embedded Systems, pages 59-62, ACM, 2019. Arrow Symbol
Kotthaus/Vitek/2019c Kotthaus, Helena and Vitek, Jan. Typical Mistakes in Data Science: Should you Trust my Model?. In Abstract Booklet of the International R User Conference (UseR!), Toulouse, France, 2019.
Kotthaus/2018a Kotthaus, Helena. Methods for Efficient Resource Utilization in Statistical Machine Learning Algorithms. TU Dortmund University, Dortmund, Department of Computer Science, 2018. Arrow Symbol
Kotthaus/etal/2018a Kotthaus, Helena and Lang, Andreas and Marwedel, Peter. Optimizing Parallel R Programs via Dynamic Scheduling Strategies. In Abstract Booklet of the International R User Conference (UseR!), Brisbane, Australia, 2018.
Kotthaus/2017b Kotthaus, Helena and Lang, Andreas and Neugebauer, Olaf and Marwedel, Peter. R goes Mobile: Efficient Scheduling for Parallel R Programs on Heterogeneous Embedded Systems. In Abstract Booklet of the International R User Conference (UseR!), pages 74, Brussels, Belgium, 2017. Arrow Symbol
Kotthaus/etal/2017a Kotthaus, Helena and Richter, Jakob and Lang, Andreas and Thomas, Janek and Bischl, Bernd and Marwedel, Peter and Rahnenführer, Jörg and Lang, Michel. RAMBO: Resource-Aware Model-Based Optimization with Scheduling for Heterogeneous Runtimes and a Comparison with Asynchronous Model-Based Optimization. In Procs. of the 11th LION, pages 180-195, 2017. Arrow Symbol
Kotthaus/etal/2016a Kotthaus, Helena and Richter, Jakob and Lang, Andreas and Lang, Michel and Marwedel, Peter. Resource-Aware Scheduling Strategies for Parallel Machine Learning R Programs through RAMBO. In Abstract Booklet of the International R User Conference (UseR!), pages 195, Stanford University, Palo Alto, California, 2016. Arrow Symbol
Richter/etal/2016b Richter, Jakob and Kotthaus, Helena and Bischl, Bernd and Marwedel, Peter and Rahnenführer, Jörg and Lang, Michel. Faster Model-Based Optimization through Resource-Aware Scheduling Strategies. In Proceedings of the 10th International Conference: Learning and Intelligent Optimization (LION 10), Vol. 10079, pages 267--273, Springer, 2016. Arrow Symbol
Kotthaus/2015a Kotthaus, Helena and Korb, Ingo and Marwedel, Peter. Performance Analysis for Parallel R Programs: Towards Efficient Resource Utilization. No. 1, Department of Computer Science 12, TU Dortmund University, 2015. Arrow Symbol
Kotthaus/etal/2014a Kotthaus, Helena and Korb, Ingo and Lang, Michel and Bischl, Bernd and Rahnenführer, Jörg and Marwedel, Peter. Runtime and Memory Consumption Analyses for Machine Learning R Programs. In Journal of Statistical Computation and Simulation, Vol. 85, No. 1, pages 14-29, 2014. Arrow Symbol
Kotthaus/etal/2014b Kotthaus, Helena and Korb, Ingo and Engel, Michael and Marwedel, Peter. Dynamic Page Sharing Optimization for the R Language. In Proceedings of the 10th Symposium on Dynamic Languages, pages 79-90, Portland, Oregon, USA, ACM, 2014. Arrow Symbol
Kotthaus/etal/2014c Kotthaus, Helena and Korb, Ingo and Künne, Markus and Marwedel, Peter. Performance Analysis for R: Towards a Faster R Interpreter. In Abstract Booklet of the International R User Conference (UseR!), pages 104, Los Angeles, USA, 2014.
Lang/etal/2014a Lang, Michel and Kotthaus, Helena and Marwedel, Peter and Weihs, Claus and Rahnenführer, Jörg and Bischl, Bernd. Automatic Model Selection for High-Dimensional Survival Analysis. In Journal of Statistical Computation and Simulation, Vol. 85, No. 1, pages 62--76, 2014. Arrow Symbol
Kotthaus/etal/2012a Kotthaus, Helena and Plazar, Sascha and Marwedel, Peter. A JVM-based Compiler Strategy for the R Language. In Abstract Booklet of the 8th International R User Conference (UseR!), pages 68, Nashville, Tennessee, USA, 2012.
Falk/etal/2011a Falk, Heiko and Kotthaus, Helena. WCET-driven Cache-aware Code Positioning. In Proceedings of the International Conference on Compilers, Architectures and Synthesis for Embedded Systems (CASES), pages 145-154, Taipei, Taiwan, 2011. Arrow Symbol

Supervised Theses