Contact

Phone: +34 91 067 3093

E-mail: bmihaljevic at fi dot upm dot es

Campus de Montegancedo s/n, Boadilla del Monte, 28660

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Position

Assistant Professor

Short Bio

Bojan Mihaljević recieved his B.Sc. degree in Computer Science and Management from the Diego Portales University in 2010. He obtained a M.Sc. degree in Artificial Intelligence in 2013 and a Ph.D. degree in Artificial Intelligence in 2018, both from from the Technical University of Madrid (UPM).

Research interests

Supervised and partially supervised classification based on probabilistic graphical models. In particular, Bayesian network classifiers and model-based classification and clustering. Supervised classification with multiple annotators. Applications of machine learning to interneuron classification.

Journal papers

  • Mihaljević, B., Benavides-Piccione, P., Bielza, C., Larrañaga, P., and DeFelipe, J. “Classification of GABAergic interneurons by leading neuroscientists”. Scientific Data 6, Article number: 221, 2019.
  • Mihaljević, B., Bielza, C., and Larrañaga, P.”bnclassify: Learning Bayesian Network Classifiers.” The R Journal, vol. 10, no. 2, pp. 455–468, 2018
  • Mihaljević, B., Larrañaga, P., Benavides-Piccione, R., Hill, S., DeFelipe, J., and Bielza, C. “Towards a supervised classification of neocortical interneuron morphologies“, BMC Bioinformatics, vol. 19, no. 1, pp. 511, 2018
  • Mihaljević, B., Benavides-Piccione, R., Guerra, L., DeFelipe, J., Larrañaga, P., Bielza, C. Classifying GABAergic interneurons with semi-supervised projected model-based clustering. Artificial Intelligence in Medicine, vol. 65, pp. 49-59, 2015,
  • Mihaljević, B., Benavides-Piccione, R., Bielza, C., DeFelipe, J., Larrañaga, P. Bayesian network classifiers for categorizing cortical GABAergic interneurons. Neuroinformatics, vol. 13, no. 2, pp. 192–208, April, 2015.
  • Mihaljević, B., Bielza, C., Benavides-Piccione, R., DeFelipe, J., Larrañaga, P. Multi-expert multi-dimensional classification of GABAergic interneurons with label Bayesian networks. Frontiers in Computational Neuroscience, vol. 8, pp. Article 150, 2014.

Book chapters

  • Mihaljević, B., Bielza, C., and Larrañaga, P. (2018). Learning Bayesian network classifiers with completed partially directed acyclic graphs. In Kratochvíl, V. and Studený, M., editors, Proceedings of the Ninth International Conference on Probabilistic Graphical Models , volume 72 of Proceedings of Machine Learning Research, pages 272–283, Prague, Czech Republic
  • Mihaljevic, B., Larrañaga, P. & Bielza, C (2013). Augmented Semi-naive Bayes Classifier. In C. Bielza et al. (editor), Advances in Artificial Intelligence, Proceedings of the 15th MultiConference of the Spanish Association for Artificial Intelligence, LNAI 8109, pages 159-167. Springer.

Workshop papers & conference abstracts

  • Mihaljevic, B., Larrañaga, P. & Bielza, C (2016). Automatic classification of cortical interneuron morphologies. Proceedings of the Workshop on Advances and Applications of Data Science & Engineering, Real Academia de Ingenieria, 2016, Madrid
  • Mihaljevic, B., Bielza, C. & Larrañaga, P. (2013). BayesClass: An R package for learning Bayesian network classifiers. Proceedings of UseR! –The R User Conference 2013, 53

Research stays

  • A three-month stay at Sean Hill’s lab at the École Polytechnique Fédérale de Lausanne

Software

  • bnclassify: an R package for discrete Bayesian network classifiers
  • Maintainer of NeuroSTR, a C++ neuroanatomy toolbox developed by Luis Rodríguez-Luján

Teaching

  • Bayesian networks: Advanced Statistics and Data Mining Summer School (2014-2018)
  • Feature selection: Advanced Statistics and Data Mining Summer School (2014-2018)
  • Bayesian network classifiers: Advanced Statistics and Data Mining Summer School (2013)
  • A workshop on Bayesian networks. Analyx® sp. z o.o. sp. k., Poznan, Poland. 14/06/2019.
  • Bayesian networks with R workshop: X Jornadas de Usuarios de R (2018), I CINCIT (2018), Fundación Barcelona Digital (2014), Real Academia de Ingenierı́a (2014)
  • Métodos supervisados, Master UniversItario en Investigación en Inteligencia Artificial

Invited talks

  • Redes Bayesianas: teoría y aplicaciones, I Congreso Internacional de Computación e Innovación Tecnológica, Andahuaylas, Perú (2018)
  • Machine Learning in Neuroscience. 4th IEEE Iberian Student Branch Congress, Madrid, Spain (2015)

Journal referee

  • Machine learning, Neuroinformatics, PLOS ONE, IEEE Access, Journal of Alzheimer’s Disease,International Journal of Approximate Reasoning