Johannes Gutenberg University Mainz
Institut für Informatik
Staudingerweg 9
55128 Mainz, Germany
E-Mail: jvexle01@uni-mainz.de
Room: 03-627
Office phone: +49-6131-39-23336
Research Interests
- Time series data mining
- Online data streams
- 3D Object classification
- Causal inference
- Deep neural networks
Activities
(Co-)Reviewing:
- IEEE International Conference on Data Mining (ICDM 2021)
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020)
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018)
- International Joint Conferences on Artificial Intelligence (IJCAI 2018)
- European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2018)
- IEEE International Conference on Big Knowledge (ICBK 2018)
Short Scientific CV
since 01/2018 Research associate at Johannes Gutenberg University in Mainz
08/2015 - 01/2016 Semester abroad at Dalarna University in Borlänge, Sweden
04/2015 - 10/2017 Computer Science (M.Sc.) at Johannes Gutenberg University in Mainz
10/2011 - 03/2015 Mathematics (B.Sc.) at Johannes Gutenberg University in Mainz
Teaching
- Data Mining Seminar at Johannes Gutenberg University in Mainz
- Machine Learning Seminar at Johannes Gutenberg University in Mainz
Publications
Garcon, A., Vexler, J., Budker, D., & Kramer, S. (2021). Deep Neural Networks to Recover Unknown Physical Parameters from Oscillating Time Series. arXiv preprint arXiv:2101.03850.
Vexler, J. and Kramer, S. (2019) Integrating LSTMs with Online Density Estimation for the Probabilistic Forecast of Energy Consumption. In: Discovery Science 22, pp. 533-543.