Matthias Aßenmacher

About

I am a postdoctoral researcher at the Chair of Statistical Learning and Data Science (Dept. of Statistics, LMU) and the NFDI Consortium for Business, Economic and Related Data (BERD@NFDI). I obtained my bachelor’s degree in Economics from LMU in 2014, afterwards I turned to Statistics (with a focus on social and economic studies) and obtained my Master’s degree in 2017 (also from LMU). In October 2021 I finished my PhD at the working group Methods for Missing Data, Model Selection and Model Averaging under the supervision of Prof. Dr. Christian Heumann with a focus on Natural Language Processing. Further I am one of the co-founders of the Open Science Initiative in Statistics (OSIS).

Contact

Institut für Statistik

Ludwig-Maximilians-Universität München

Ludwigstraße 33

D-80539 München

matthias [at] stat.uni-muenchen.de

Teaching

Thesis supervision

If you are interested in writing your thesis under my supervision, please send me your field of interest and your ideas, a CV and your current transcript of records.
A selection of theses I recently supervised (together with Christian Heumann) can be found here.

Research Interests

My main research interest are:

Other topics that interest me:

You Can Find me on

References

  1. Aßenmacher M, Dietrich M, Elmaklizi A, Hemauer EM, Wagenknecht N (2022) Whitepaper: New Tools for Old Problems.
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  2. Koch P, Aßenmacher M, Heumann C (2022) Pre-trained language models evaluating themselves - A comparative study Proceedings of the Third Workshop on Insights from Negative Results in NLP, pp. 180–187. Association for Computational Linguistics, Dublin, Ireland.
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  3. Aßenmacher M, Schulze P, Heumann C (2021) Benchmarking down-scaled (not so large) pre-trained language models Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021), pp. 14–27. KONVENS 2021 Organizers, Düsseldorf, Germany.
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  4. Aßenmacher M, Corvonato A, Heumann C (2021) Re-Evaluating GermEval17 Using German Pre-Trained Language Models Proceedings of the Swiss Text Analytics Conference 2021, CEUR Workshop Proceedings, Winterthur, Switzerland (Online).
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  5. Schulze P, Wiegrebe S, Thurner PW, Heumann C, Aßenmacher M, Wankmüller S (2021) Exploring Topic-Metadata Relationships with the STM: A Bayesian Approach. arXiv preprint arXiv:2104.02496.
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  6. Lebmeier E, Hou N, Spann K, Aßenmacher M (2021) Creating a Customer Centricity Graph from unstructured customer feedback. Applied Marketing Analytics 6, 221–229.
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  7. Meidinger M, Aßenmacher M (2021) A New Benchmark for NLP in Social Sciences: Evaluating the Usefulness of Pre-trained Language Models for Classifying Open-ended Survey Responses Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, pp. 866–873. SciTePress.
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  8. Schiergens TS, Drefs M, Dörsch M et al. (2021) Prognostic Impact of Pedicle Clamping during Liver Resection for Colorectal Metastases. Cancers 13, 72.
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  9. Guderlei M, Aßenmacher M (2020) Evaluating Unsupervised Representation Learning for Detecting Stances of Fake News Proceedings of the 28th International Conference on Computational Linguistics, pp. 6339–6349. International Committee on Computational Linguistics, Barcelona, Spain (Online).
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  10. Viellieber VD, Aßenmacher M (2020) Pre-trained language models as knowledge bases for Automotive Complaint Analysis. arXiv preprint arXiv:2012.02558.
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  11. Aßenmacher M, Heumann C (2020) On the comparability of pre-trained language models Proceedings of the 5th Swiss Text Analytics Conference and 16th Conference on Natural Language Processing, CEUR Workshop Proceedings, Zurich, Switzerland (Online).
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  12. Aßenmacher M, Kaiser JC, Zaballa I, Gasparrini A, Küchenhoff H (2019) Exposure-lag-response associations between lung cancer mortality and radon exposure in German uranium miners. Radiation and Environmental Biophysics.
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  13. Sint A, Lutz R, Assenmacher M et al. (2019) Monocytic HLA-DR expression for prediction of anastomotic leak after colorectal surgery. Journal of the American College of Surgeons 229, 200–209.
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  14. Deffner V, Kreuzer M, Sobotzki C et al. (2019) Uncertainties in radiation exposure assessment in the Wismut cohort: a preliminary evaluation BIO Web of Conferences, p. 03009. EDP Sciences.
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  15. Küchenhoff H, Deffner V, Aßenmacher M et al. (2018) Ermittlung der Unsicherheiten der Strahlenexpositionsabschätzung in der Wismut-Kohorte-Teil I-Vorhaben 3616S12223.
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  16. Brandl C, Breinlich V, Stark KJ et al. (2016) Features of age-related macular degeneration in the general adults and their dependency on age, sex, and smoking: results from the German KORA study. PloS one 11, e0167181.
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