At a general level, my research interests are focused around developing and applying statistical and machine learning methods for real-world applications. Some key topics are:
Statistical machine learning
Probabilistic graphical models
Network structure learning
Computational causal inference
I completed my PhD in statistics in 2016 at Åbo Akademi University (Finland), in which I developed a new class of probabilistic graphical models, along with algorithms for learning the structure of the models from data. During 2016-2020, I worked as a postdoc at University of Helsinki (Finland), developing and applying data analysis tools, primarily for applications in bacterial statistical genomics. Since February 2020, I have been working at UiO as an Associate Professor in Statistics and Data Science.
- STK4011 - Statistical Inference Theory (Autumn 2020-21).
- STK4290 - Probabilistic Graphical Models (Spring 2021).
Supervision (PhD students)
- Anders Hjort (Department of Mathematics, Eiendomsverdi AS, 2020-): Uncertainty in house price prediction (Industrial PhD).
- Juri Kuronen (Department of Biostatistics, 2018-): High-dimensional structure learning of Markov networks with applications in bacterial statistical genomics.
- Ghadi Al Hajj (Department of Informatics, 2020-): Improving generalization of machine learning models in medical image and immune receptor sequence analysis through the incorporation of domain priors and constraints.
Finnish Statistical Society - Doctoral Thesis Award (2013-2016).
For a complete list, see my profile at Google Scholar.
Pavlović, Milena; Scheffer, Lonneke; Motwani, Keshav; Kanduri, Chakravarthi; Kompova, Radmila & Vazov, Nikolay Aleksandrov [Show all 41 contributors for this article] (2021). The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires. Nature Machine Intelligence. 3, p. 936–944. doi: 10.1038/s42256-021-00413-z.
Chewapreecha, Claire; Pensar, Johan; Chattagul, Supaksorn; Pesonen, Maiju; Sangphukieo, Apiwat & Boonklang, Phumrapee [Show all 18 contributors for this article] (2021). Co-evolutionary Signals Identify Burkholderia pseudomallei Survival Strategies in a Hostile Environment. Molecular Biology and Evolution (MBE). ISSN 0737-4038. doi: 10.1093/molbev/msab306.
Suotsalo, Kimmo; Xu, Yingying; Corander, Jukka & Pensar, Johan (2021). High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood. Statistics and computing. ISSN 0960-3174. 31(73). doi: 10.1007/s11222-021-10049-z.
Mageiros, Leonardos; Meric, Guillaume; Bayliss, Sion; Pensar, Johan; Pascoe, Ben & Mourkas, Evangelos [Show all 19 contributors for this article] (2021). Genome evolution and the emergence of pathogenicity in avian Escherichia coli. Nature Communications. ISSN 2041-1723. 12(1), p. 1–13. doi: 10.1038/s41467-021-20988-w.
Tadei, Alessandro; Haajanen, Juulia; Pensar, Johan; Santtila, Pekka & Antfolk, Jan (2020). Counteracting deceptive responding in the Finnish Investigative Instrument of Child Sexual Abuse (FICSA). Journal of Sexual Aggression. ISSN 1355-2600. doi: 10.1080/13552600.2020.1846802. Full text in Research Archive
Top, Janetta; Arredondo-Alonso, Sergio; Schürch, Anita C.; Puranen, Santeri; Pesonen, Maiju & Pensar, Johan [Show all 8 contributors for this article] (2020). Genomic rearrangements uncovered by genome-wide co-evolution analysis of a major nosocomial pathogen, Enterococcus faecium. Microbial Genomics. ISSN 2057-5858. 6(12), p. 1–8. doi: 10.1099/mgen.0.000488. Full text in Research Archive