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Dr Jacob Montiel

Postdoctoral Fellow (Computer Science)

Qualifications: PhD UPS-TPT

Contact Details

Email: jmontiel@waikato.ac.nz
Room: FG.2.04
Phone: +64 7 837 9641
Website: https://jacobmontiel.github.io/

About Jacob

I am a Research Fellow in the Machine Learning Group at the University of Waikato. I am the lead developer and maintainer of scikit-multiflow, a machine learning framework for multi-label/multi-output stream data.

I worked at GE Aviation as Tech Lead in the development of embedded software for Diagnostics and Prognostics of Airborne Systems.

Recent Publications

  • Togbe, M., Barry, M., Boly, A., Chabchoub, Y., Chiky, R., Montiel Lopez, J., & Vinh-Thuy, T. (2020). Anomaly detection for data streams based on isolation forest using scikit-multiflow. In The 20th International Conference on Computational Science and its Applications (ICCSA 2020). , Caligari, Italy. Retrieved from https://hal.archives-ouvertes.fr/hal-02874869/document

  • Montiel, J. (2020). Learning from evolving data streams. In Proceedings of the 19th Python in Science Conference. SciPy. doi:10.25080/majora-342d178e-00a

  • Yogarajan, V., Montiel, J., Smith, T., & Pfahringer, B. (2020). Seeing The Whole Patient: Using Multi-Label Medical Text Classification Techniques to Enhance Predictions of Medical Codes.. CoRR, abs/2004.00430.

  • Montiel, J., Bifet, A., Losing, V., Read, J., & Abdessalem, T. (2019). Learning fast and slow: A unified batch/stream framework. In Proc 2018 IEEE International Conference on Big Data (Big Data 2018) (pp. 1065-1072). Seattle, WA, USA. doi:10.1109/BigData.2018.8622222

Find more research publications by Jacob Montiel