Research/art/teacher profile of a person
Name and surname:
Mgr. Vladimír Boža, PhD.
Document type:
Research/art/teacher profile of a person
The name of the university:
Comenius University Bratislava
The seat of the university:
Šafárikovo námestie 6, 818 06 Bratislava

I. - Basic information

I.1 - Surname
Boža
I.2 - Name
Vladimír
I.3 - Degrees
Mgr., PhD.
I.4 - Year of birth
1989
I.5 - Name of the workplace
Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava
I.6 - Address of the workplace
Mlynská dolina F1 842 48 Bratislava
I.7 - Position
Postdoc
I.8 - E-mail address
boza1@uniba.sk
I.9 - Hyperlink to the entry of a person in the Register of university staff
https://www.portalvs.sk/regzam/detail/28543?do=filterForm-submit&name=Vladim%C3%ADr&surname=Bo%C5%BEa&sort=surname&employment_state=yes&filter=Vyh%C4%BEada%C5%A5
I.10 - Name of the study field in which a person works at the university
Computer Science
I.11 - ORCID iD
0000-0002-0618-1557

II. - Higher education and further qualification growth

II.1 - First degree of higher education
II.a - Name of the university or institution
Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava
II.b - Year
2011
II.c - Study field and programme
Computer Science
II.2 - Second degree of higher education
II.a - Name of the university or institution
Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava
II.b - Year
2013
II.c - Study field and programme
Computer Science
II.3 - Third degree of higher education
II.a - Name of the university or institution
Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava
II.b - Year
2017
II.c - Study field and programme
Computer Science
II.4 - Associate professor
II.5 - Professor
II.6 - Doctor of Science (DrSc.)

III. - Current and previous employment

III.a - Occupation-position III.b - Institution III.c - Duration
Assistant professor Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava 2017 - now

IV. - Development of pedagogical, professional, language, digital and other skills

IV.a - Activity description, course name, other IV.b - Name of the institution IV.c - Year
English Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava 2008

V. - Overview of activities within the teaching career at the university

V.1 - Overview of the profile courses taught in the current academic year according to study programmes
V.2 - Overview of the responsibility for the delivery, development and quality assurance of the study programme or its part at the university in the current academic year
V.3 - Overview of the responsibility for the development and quality of the field of habilitation procedure and inaugural procedure in the current academic year
V.4 - Overview of supervised final theses
V.4.1 - Number of currently supervised theses
V.4.a - Bachelor's (first degree)
0
V.4.b - Diploma (second degree)
5
V.4.c - Dissertation (third degree)
0
V.4.2 - Number of defended theses
V.4.a - Bachelor's (first degree)
5
V.4.b - Diploma (second degree)
4
V.4.c - Dissertation (third degree)
0
V.5 - Overview of other courses taught in the current academic year according to study programmes
V.5.a - Name of the course V.5.b - Study programme V.5.c - Degree V.5.d - Field of study
Principles of Data Science Data Science I. Computer Science
Data Management Data Science I. Computer Science
Time-Restricted Programming (1) Informatics I. Computer Science
Time-Restricted Programming (2) Informatics I. Computer Science
Time-Restricted Programming (3) Informatics I. Computer Science
Time-Restricted Programming (4) Informatics I. Computer Science
Time-Restricted Programming (5) Informatics I. Computer Science
Current Approaches in Machine Learning Informatics II. Computer Science
Machine Learning Informatics II. Computer Science

VI. - Overview of the research/artistic/other outputs

VI.1 - Overview of the research/artistic/other outputs and the corresponding citations
VI.1.1 - Number of the research/artistic/other outputs
VI.1.a - Overall
35
VI.1.b - Over the last six years
28
VI.1.2 - Number of the research/artistic/other outputs registered in the Web of Science or Scopus databases
VI.1.a - Overall
20
VI.1.b - Over the last six years
14
VI.1.3 - Number of citations corresponding to the research/artistic/other outputs
VI.1.a - Overall
638
VI.1.b - Over the last six years
516
VI.1.4 - Number of citations registered in the Web of Science or Scopus databases
VI.1.a - Overall
334
VI.1.b - Over the last six years
284
VI.1.5 - Number of invited lectures at the international, national level
VI.1.a - Overall
1
VI.1.b - Over the last six years
1
VI.2 - The most significant research/artistic/other outputs
1

Boža, V., Brejová, B., & Vinař, T. (2017). DeepNano: deep recurrent neural networks for base calling in MinION nanopore reads. PloS one, 12(6), e0178751.

2

Kvapilova, L., Boza, V., Dubec, P., Majernik, M., Bogar, J., Jamison, J., ... & Karlin, D. R. (2019). Continuous sound collection using smartphones and machine learning to measure cough. Digital biomarkers, 3(3), 166-175.

3

Boža, V., Perešíni, P., Brejová, B., & Vinař, T. (2020). DeepNano-blitz: a fast base caller for MinION nanopore sequencers. Bioinformatics, 36(14), 4191-4192.

4

Boža, Vladimír, and Vladimír Macko. "Two Sparse Matrices are Better than One: Sparsifying Neural Networks with Double Sparse Factorization." In The Thirteenth International Conference on Learning Representations. 2025.

5

Perešíni, P., Boža, V., Brejová, B., & Vinař, T. (2021). Nanopore base calling on the edge. Bioinformatics, 37(24), 4661-4667.

VI.3 - The most significant research/artistic/other outputs over the last six years
1

Herman, Robert, et al. "International evaluation of an artificial intelligence–powered electrocardiogram model detecting acute coronary occlusion myocardial infarction." European Heart Journal-Digital Health 5.2 (2024): 123-133.

2

Kvapilova, L., Boza, V., Dubec, P., Majernik, M., Bogar, J., Jamison, J., ... & Karlin, D. R. (2019). Continuous sound collection using smartphones and machine learning to measure cough. Digital biomarkers, 3(3), 166-175.

3

Boža, Vladimír, and Vladimír Macko. "Two Sparse Matrices are Better than One: Sparsifying Neural Networks with Double Sparse Factorization." In The Thirteenth International Conference on Learning Representations. 2025.

4

Perešíni, P., Boža, V., Brejová, B., & Vinař, T. (2021). Nanopore base calling on the edge. Bioinformatics, 37(24), 4661-4667.

5

Boza, Vladimir, et al. "Dynamic Pooling Improves Nanopore Base Calling Accuracy." IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021).

VI.4 - The most significant citations corresponding to the research/artistic/other outputs
1

Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., ... & Greene, C. S. (2018). Opportunities and obstacles for deep learning in biology and medicine. Journal of The Royal Society Interface, 15(141), 20170387.

2

Simpson, J. T., & Pop, M. (2015). The theory and practice of genome sequence assembly. Annual review of genomics and human genetics, 16, 153-172.

3

Garalde, D. R., Snell, E. A., Jachimowicz, D., Sipos, B., Lloyd, J. H., Bruce, M., ... & Turner, D. J. (2018). Highly parallel direct RNA sequencing on an array of nanopores. Nature methods, 15(3), 201-206.

4

Eraslan, G., Avsec, Ž., Gagneur, J., & Theis, F. J. (2019). Deep learning: new computational modelling techniques for genomics. Nature Reviews Genetics, 20(7), 389-403.

5

Wick, R. R., Judd, L. M., & Holt, K. E. (2019). Performance of neural network basecalling tools for Oxford Nanopore sequencing. Genome biology, 20(1), 1-10.

VI.5 - Participation in conducting (leading) the most important research projects or art projects over the last six years
1

Vladimír Boža (vedúci): Rýchle rozpoznávanie báz pre nanopórový sekvenántor MinION / Vladimír Boža (leading): Fast base callers for MinION nanopore sequencers, Google Cloud Computing Grant

2

Vladimír Boža (účasť): Chyby a neurčitosť v sekvenovaní DNA: Algoritmy a modely (vedúci Tomáš Vinař, Mária Lucká), VEGA 1/0458/18 / Vladimír Boža (participation): Error and uncertainty in DNA sequencing: algorithms and models (principal investigators Tomáš Vinař, Mária Lucká)

3

Vladimír Boža (účasť): Nekonvenčné aplikácie nových sekvenačných technológií v komparatívnej a funkčnej genomike (vedúci Jozef Nosek, Tomáš Vinař), APVV-18-0239 / Vladimír Boža (participation): Non-conventional applications of emerging sequencing technologies in comparative and functional genomics (principal investigators Jozef Nosek, Tomáš Vinař), APVV-18-0239


VII. - Overview of organizational experience related to higher education and research/artistic/other activities

VII.a - Activity, position VII.b - Name of the institution, board VII.c - Duration
Program commitee member International Conference on Artificial Neural Networks 2021

VIII. - Overview of international mobilities and visits oriented on education and research/artistic/other activities in the given field of study

VIII.a - Name of the institution VIII.b - Address of the institution VIII.c - Duration (indicate the duration of stay) VIII.d - Mobility scheme, employment contract, other (describe)
Google Zurich, Switzerland July 2010 - September 2010 internship
Google Zurich, Switzerland June 2011 - September 2011 internship

IX. - Other relevant facts

IX.a - If relevant, other activities related to higher education or research/artistic/other activities are mentioned

Grandmaster in data science competitions on Kaggle.com

Date of last update
2025-05-27