Jannes Münchmeyer

Phd student

Machine learning researcher @ GFZ Potsdam and HU Berlin in the HEIBRiDS graduate school; Working on fast assessment of earthquakes

Previously working on BioNLP and gene regulatory networks

Research interests

Earthquake early warning

Probabilistic machine learning

Earthquake nucleation

Uncertainty quantification

Magnitude scale calibration

Domain adaptation and transfer learning



Münchmeyer, J., Bindi, D., Leser, U., & Tilmann, F. (2021). Earthquake magnitude and location estimation from real time seismic waveforms with a transformer network. arxiv preprint. [paper] [code]

Weber, L., Sänger, M., Münchmeyer, J., Habibi, M., Leser, U., & Akbik, A. (2021). HunFlair: An Easy-to-Use Tool for State-of-the-Art Biomedical Named Entity Recognition. Bioinformatics. [paper] [code]


Münchmeyer, J., Bindi, D., Leser, U., & Tilmann, F. (2020). The transformer earthquake alerting model: A new versatile approach to earthquake early warning. Geophysical Journal International. [paper] [code]


Münchmeyer, J., Bindi, D., Sippl, C., Leser, U., & Tilmann, F. (2019). Low uncertainty multifeature magnitude estimation with 3-D corrections and boosting tree regression: application to North Chile. Geophysical Journal International, 220(1), 142-159. [paper] [code]

Weber, L.*, Münchmeyer, J.*, Rocktäschel, T., Habibi, M., & Leser, U. (2019). HUNER: Improving Biomedical NER with Pretraining. Bioinformatics. *: Equal contribution [paper] [code]

Weber, L., Minervini, P., Münchmeyer, J., Leser, U., & Rocktäschel, T. (2019). NLprolog: Reasoning with Weak Unification for Question Answering in Natural Language. ACL 2019, Florence, Italy. [paper] [code]


Trescher, S., Münchmeyer, J., & Leser, U. (2017). Estimating genome-wide regulatory activity from multi-omics data sets using mathematical optimization. BMC systems biology, 11(1), 41. [paper]

Conference contributions


Münchmeyer, J., Bindi, D., Leser, U., & Tilmann, F. (2020). The Transformer Earthquake Alerting Model: Improving Earthquake Early Warning with Deep Learning. AGU virtual conference 2020. [recorded talk]

Münchmeyer, J., Bindi, D., Leser, U., & Tilmann, F. (2020). End-to-end PGA estimation for earthquake early warning using transformer networks. EGU virtual conference 2020. [presentation slides]


Münchmeyer, J., Bindi, D., Leser, U., & Tilmann, F. J. (2019). Convolutional event embeddings for fast probabilistic earthquake assessment. AGU Fall Meeting 2019, San Francisco, USA.

Münchmeyer, J., Bindi, D., Sippl, C., & Tilmann, F. (2019). Increasing magnitude scale consistency by combining multiple waveform features through machine learning. EGU General Assembly 2019, Vienna, Austria.

Professional activities


Convened session "Data Science and Machine Learning for Natural Hazards and Seismology" at EGU virtual conference 2020 together with Tang, H., Chen, K., Olen, S. & Corbi, F. [link]


munchmej (at) gfz-potsdam (dot) de