Bruno Frederik Bauwens
- Associate Professor: Faculty of Computer Science / Big Data and Information Retrieval School
- Research Fellow: Faculty of Computer Science / Big Data and Information Retrieval School / Laboratory of Theoretical Computer Science
- Bruno Frederik Bauwens has been at HSE University since 2015.
Education and Degrees
Ghent University
Ghent University
Ghent University
Ghent University
Supervisor of the following Doctoral theses
- 1Y. Ivanashev Classification and Study of Сomplexity Properties Of Problems that are Associated with Counting of The Number of Paths of Nondeterministic Algorithms
Courses (2023/2024)
- Computational Complexity Theory (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Eng
- Statistical Learning Theory (Bachelor’s programme; Faculty of Computer Science; 4 year, 1, 2 module)Eng
- Statistical Learning Theory (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Eng
- Theoretical Informatics (Postgraduate course field of study Postgraduate Studies, field of study Postgraduate Studies; 1 year, 1 semester)Eng
- Theory of Computation (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Eng
- Past Courses
Courses (2022/2023)
- Computational Complexity Theory (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Eng
- Statistical Learning Theory (Bachelor’s programme; Faculty of Computer Science; 4 year, 1, 2 module)Eng
- Statistical Learning Theory (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Eng
- Statistical Learning Theory (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Eng
- Statistical Learning Theory (Mago-Lego; 1, 2 module)Eng
- Theoretical Computer Science 2 (Postgraduate course; Faculty of Computer Science; 2 year, 1 semester)Eng
- Theoretical Informatics (Postgraduate course; 1 year, 1 semester)Eng
- Theory of Computation (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Eng
- Theory of Computation (Master’s programme; Faculty of Computer Science; 1 year, 1, 2 module)Rus
Courses (2021/2022)
- Statistical Learning Theory (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Eng
- Statistical Learning Theory (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Eng
- Statistical Learning Theory (Bachelor’s programme; Faculty of Computer Science; 4 year, 1, 2 module)Eng
- Theory of Computation (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Eng
- Theory of Computation (Master’s programme; Faculty of Computer Science; 1 year, 1, 2 module)Eng
Courses (2020/2021)
- Research Seminar (Postgraduate course; Faculty of Computer Science; 3 year, 1, 2 semester)Rus
- Research Seminar (Postgraduate course; Faculty of Computer Science field of study Computer and Information Scienc, field of study Informatics and Computer Engineering; 2 year, 2 semester)Rus
- Research Seminar (Postgraduate course; Faculty of Computer Science field of study Computer and Information Scienc, field of study Informatics and Computer Engineering)Eng
- Statistical Learning Theory (Bachelor’s programme; Faculty of Computer Science; 4 year, 1, 2 module)Eng
- Statistical Learning Theory (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Eng
- Statistical Learning Theory (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Eng
- Theoretical Computer Science (Postgraduate course; Faculty of Computer Science field of study Computer and Information Scienc, field of study Informatics and Computer Engineering; 2 year, 1 semester)Eng
- Theory of Computation (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Eng
- Theory of Computation (Master’s programme; Faculty of Computer Science; 1 year, 1, 2 module)Eng
Conferences
Papers in refereed international conferences 1. BB and M. Zimand. Linear list-approximation for short programs (or the power of a few random bits). In the 29th Conference on Computational Complexity (CCC 2014), November 2013 2. BB. Asymmetry of the Kolmogorov complexity of online predicting odd and even bits. In the 31st International Symposium on Theoretical Aspects of Computer Science (STACS 2014), volume 25 of Leibniz International Proceedings in Informatics (LIPIcs), pages 125–136, Dagstuhl, Germany, 2014 3. BB, A. Makhlin, N. Vereshchagin, and M. Zimand. Short lists with short programs in short time. In the 28th Conference on Computational Complexity (CCC 2013), June 2013 4. BB. Complexity of complexity and maximal plain versus prefix-free Kolmogorov complexity. In Proceedings of the 39th International Colloquium on Automata, Languages and Programming (ICALP 2012), February 2012 5. BB. m-sophistication. In Proceedings of the 6th Conference on Computability in Europe (CiE 2010), July 2010 6. D. Devlaminck, W. Waegeman, BB, B. Wyns, G. Otte, and P. Santens. From circular ordinal regression to multilabel classification. In ECML 2010 Workshop on Preference Learning, Barcelona, Spain, September 2010 7. D. Devlaminck, W. Waegeman, B.Bauwens, B.Wyns, G.Otte, L.Boullart, and P.Santens. Directional predictions for 4-class bci data. In Proceedings of the 18th conference on Artificial Neural Networks, Computational intelligence, and Machine learning, pages 153–158, Brugge, April 2009 8. H. Cani`ere, BB, C. T’Joen, L. Boullart, and M. De Paepe. Classification of horizontal two-phase flow using support vector machines with capacitance signals. In Proceedings of the IIR International Congress of Refrigeration, pages 21–26, 2007 9. H. Cani`ere, BB, C. T’Joen, A. Willockx, L. Boullart, and M. De Paepe. Horizontal two-phase flow characterisation and classification based on capacitance measurements. In Proceedings of the 5th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, 2007 10. BB, B. Wyns, D. Devlaminck, G. Otte, L. Boullart, and P. Santens. Mutual information and algorithmic information transfer as ideal undirected and directed independence tests. In Proceedings of the 2007 International Conference on Foundations of Computer Science, LasVegas, 2007 11. BB, B. Wyns, D. Devlaminck, G. Otte, L. Boullart, and P. Santens. Measuring instantaneous directed dependencies in interacting oscillators. In Proceedings of the 28th Symposium on Information Theory
Grants
Causality between EEG and deep brain signals, theory and application: Phd grant for Flanders Institute for Technology and Innovation.
Design educational interactive applets for exercises in mathematical analysis: grant from the science education fund (10 000 euro).
Kolmogorov complexity, induction and applications to probabilistic inductive logical programming: a grant from the Portuguese Science Foundation (20 000 euro).
Employment history
Teaching 2/2006-8/2008 Introduction to computer science for medical engineers, signal processing part (both theory and exercises) Spring 2009 Probability and statistics for civil engineers, exercises
2/2010-6/2011 Teaching assistant (help with exercises, theory, and study attitude) for freshmen: basic mathematics, analysis, algebra, geometry, physics in the faculty of engineering and architecture, all physics courses in the faculty of sciences
2/2014-4/2014 Physics in high school Sint-Pieterscollege (highest grade, in classes focussed on science and math)
6/2014– Co-lecturer for the course “Complexity and Computability” Teaching assistant for the course “Programming in Python”
10/2014–11/2014 Interim replacement of a lecturer mathematics (teaching pre-calculus and calculus to students in the major of commercial sciences)
11/2015–5/2016 Theoretical computer science to Phd students
'I’m impressed by the mathematical history and general level of mathematical skills here in Moscow'
Bruno Bauwens, an expert in Kolmogorov complexity, is a new recruit at the HSE Faculty of Computer Science. He started in September 2015. Bruno received his PhD from Ghent University in Belgium, after which he held postdoctoral fellowships at Porto University (Portugal), as well as at the University of Montpellier and University of Lorraine.
International Experts in the Faculty of Computer Science
An important step in integrating the university into the global educational, scientific and research space is the expansion of international recruiting. Since its very first year, the Faculty of Computer Science at the Higher School of Economics has had a foreign professor working on staff. In 2015, four internationally recruited experts teach and conduct research in the faculty.
International Experts in the Faculty of Computer Science
An important step in integrating the university into the global educational, scientific and research space is the expansion of international recruiting. Since its very first year, the Faculty of Computer Science at the Higher School of Economics has had a foreign professor working on staff. In 2015, four internationally recruited experts teach and conduct research in the faculty.