Julian Vexler, M.Sc.

Johannes Gutenberg University Mainz
Institut für Informatik
Staudingerweg 9
55128 Mainz, Germany

E-Mail:
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.