Contact:
| Address: |
Postal Address Humboldt-Universität zu Berlin Department of Computer Science Unter den Linden 6 10099 Berlin Visiting Address |
| Phone: |
030-2093-41287 |
| EMail: |
patrick.schaefer
hu-berlin.de
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Google Scholar |
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DBLP |
| 0000-0003-2244-6065 | |
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Github Profile |
Teaching:
Source codes and Frameworks:
- Java: Scalable Time Series Data Analytics using SFA, BOSS, BOSS VS and WEASEL
- Python: Motiflets - Time Series Motif Discovery
- Python: Leitmotifs - Subdimensional Time Series Motif Discovery
- Python: WEASEL v1 and v2, SFA, BOSS - Time Series Classification
- Python: ClaSP - Time Series Segmentation
- C: SOFA - Exact Time Series Similarity Search Index
- aeon - A unified framework for machine learning with time series.
Selected Publications
2025
- P. Schäfer, J. Brand, U. Leser, P. Botao, and T. Palpanas. Fast and Exact Similarity Search in less than a Blink of an Eye, ICDE 2025, Hong Kong SAR, China. (accepted) (Code)
- P. Schäfer, U. Leser, Discovering Leitmotifs in Multidimensional Time Series, PVLDB, London, UK, 2025. (Paper, Webpage/Code)
- A. Ermshaus, P. Schäfer, U. Leser. CLaP -- State Detection from Time Series, Prepint. (Paper-Draft)
2024
- P. Schäfer, J. Brand, U. Leser, P. Botao, T. Palpanas. Fast and Exact Similarity Search in less than a Blink of an Eye, Prepint. (Paper-Draft, Code)
- Middlehurst, M., Ismail-Fawaz, A., Guillaume, A., Holder, C., Rubio, D. G., Bulatova, G., Tsaprounis, L., Mentel, L., Walter, M., Schäfer, P., and Bagnall, A., aeon: a Python Toolkit for Learning from Time Series, Journal of Machine Learning Research, 2024. (Paper)
- Bagnall, A., Middlehurst, M., Forestier, G., Ismail-Fawaz, A., Guillaume, A., Rubio, D. G., Ermshaus, A., Schäfer, P., Papenbrock, T., Schmidl, S., and Wenig, P., An Introduction to Machine Learning from Time Series, Tutorial@ECML-PKDD, 2024.
- A. Ermshaus, P. Schäfer, U. Leser, Raising the ClaSS of Streaming Time Series Segmentation, PVLDB, Guangzhou, China, 2024. (Webpage, Paper)
- Matthew Middlehurst, Patrick Schäfer, Anthony J. Bagnall, Bake off redux: a review and experimental evaluation of recent time series classification algorithms,
Data Min Knowl Disc, 2024. (Webpage, Paper)
2023
- A. Ermshaus, P. Schäfer, U. Leser, ClaSP: parameter-free time series segmentation, Data Min Knowl Disc, 2023. (Webpage, Paper, Code)
- P. Schäfer, U. Leser, WEASEL 2.0 - A Random Dilated Dictionary Transform for Fast, Accurate and Memory Constrained Time Series Classification, Journal Track @ ECML/PKDD 2023. (Paper, Webpage/Code)
- P. Schäfer, U. Leser, Motiflets - Simple and Accurate Detection of Motifs in Time Series, PVLDB, Vancouver, Canada, 2023. (Webpage, Paper, Code)
2022
- A. Ermshaus, P. Schäfer, U. Leser, Window Size Selection In Unsupervised Time Series Analytics: A Review and Benchmark, AALTD @ ECML/PKDD, 2022, (Paper, Webpage/Code)
2021
- P. Schäfer, A. Ermshaus, U. Leser, ClaSP - Time Series Segmentation, CIKM, Virtual, 2021(Webpage, Paper, Code)
2020
- P. Schäfer, U. Leser, TEASER: Early and Accurate Time Series Classification, ECML / PKDD, Virtual, 2020. (Webpage, Paper, Code)
2019
- S. Sprenger, P. Schäfer, Ulf Leser, BB-Tree: A practical and efficient main-memory index structure for multidimensional workloads. Int. Conf. on Extending Database Technologies (EDBT) Lisbon, Portugal, 2019. (Paper)
- S. Sprenger, P. Schäfer, Ulf Leser, BB-Tree: A main-memory index structure for multidimensional range queries (short paper). ICDE, Macau, China, 2019.
2018
- P. Schäfer, Ulf Leser, Multivariate Time Series Classification with WEASEL+MUSE, 3rd ECML/PKDD Workshop on AALTD, 2018. (Paper, Code)
- S. Sprenger, P. Schäfer, Ulf Leser, Multidimensional Range Queries on Modern Hardware, Prepint. (Paper)
- P. Schäfer, Dirk Pflugmacher, Patrick Hostert, Ulf Leser, Classifying land cover from satellite images using time series analytics, Workshop Proceedings of the EDBT/ICDT 2018. (Paper)
- P. Schäfer, Ulf Leser, Multivariate Time Series Classification with WEASEL+MUSE, Prepint. (Webpage, Paper, Code)
2017
- P. Schäfer, Ulf Leser, Fast and Accurate Time Series Classification with WEASEL, CIKM 2017. (Webpage, Paper, Code)
- P. Schäfer, Ulf Leser, Benchmarking Univariate Time Series Classifiers, BTW 2017 (Paper)
2016
- P. Schäfer, Scalable Time Series Classification, ECML/PKDD 2016, Data Min Knowl Disc 2016 (Webpage, Paper, Keynote, PPT, Code)
2015
- P. Schäfer, Scalable Time Series Classification for Data Analytics, Dissertation 2015, (Dissertation, Keynote, PPT)
2014
- P. Schäfer, The BOSS is concerned with time series classification in the presence of noise, Data Min Knowl Disc 2014, (Webpage, Paper, Code)
- P. Schäfer, Experiencing the Shotgun Distance for Time Series Analysis, Transactions MLDM 2014, (Webpage, Paper, Code)
- I. Potamitis, P. Schäfer, On classifying insects from their wing-beat: New results, Ecology and acoustics: emergent properties from community to landscape, Paris, France 2014.
- P. Schäfer, Towards Time Series Classification without Human Preprocessing, MLDM 2014, (Webpage, Paper, Code)
2013
- P. Schäfer, Shooting Audio Recordings of Insects with SFA, AmiBio Workshop 2013.
- P. Schäfer, S. Dressler, SFA : a symbolic fourier approximation and index for similarity search in high dimensional datasets, EDBT 2012, (Webpage, Paper, Code)
Organization
"Advanced Analytics and Learning on Temporal Data"
Research Interests:
- Big Data Analytics
- Time Series: Classification, Motif Discovery, Segmentation
- Information Retrieval
- NoSQL
Reviewer & Program Committee:
- KDD '25
- VLDB '25 - '26
- ECML since '21 - '24
- AAAI '21 - '23
- IJCAI '20
- ADBIS '20
- AALTD since '16 - "Advanced Analytics and Learning on Temporal Data"
- LDWA '19 - "Large-Scale Data Management and Processing - Applications in Research and Industry"
- IEEE/CAA '19 - Special Issue on Time Series Classification
- TKDE, since '17
- Data Min Knowl Disc (Journal), since '16
- IEEE Cybernetics, since '18
Current Projects:
- aeon (Core developer)
Past Projects:
- sktime (Former Core developer)
- MoSGrid
- Harness
- Contrail
- XtreemFS