Kailash Budhathoki

I am interested in Algorithmic Data Analysis where we are concerned with developing theory and algorithms for extracting interesting structures from data. My past and current research mainly concerns with discovering assocations, correlations, and causation from data by means of (algorithmic) information theory. I also closely follow the developments in design and visualisation.

Publications
  • 2018

    Causal Inference on Event Sequences, Corrigendum

    In: Proceedings of the SIAM International Conference on Data Mining (SDM'18), SIAM, 2018.

  • 2017

    ORIGO: Causal Inference by Compression

    Knowledge and Information Systems, Springer, 2017.


    MDL for Causal Inference on Discrete Data

    In: Proceedings of the IEEE International Conference on Data Mining (ICDM'17), IEEE, 2017.


    Correlation by Compression

    In: Proceedings of the SIAM International Conference on Data Mining (SDM'17), SIAM, 2017.

  • 2016

    Casual Inference by Compression, Corrigendum

    In: Proceedings of the IEEE International Conference on Data Mining (ICDM'16), IEEE, 2016.

  • 2015

    The Difference and The Norm — Characterising Similarities and Differences between Databases

    In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Springer, 2015.

Degree
  • Dec 2015 — Current

    PhD Student

    Max Planck Institute for Informatics and Saarland University, Germany

  • Oct 2013 — Sep 2015

    MSc in Computer Science

    Saarland University, Germany

  • Dec 2006 — Dec 2010

    Bachelor of Computer Engineering

    Institute of Engineering, Pulchowk Campus, Nepal

Teaching
Misc
Blog Posts

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