Dr Bjorn Jensen

  • Lecturer in Computing Science (Computing Science)

telephone: 0141 330 1639
email: Bjorn.Jensen@glasgow.ac.uk

SAWB, Room 306, School of Computing Science

ORCID iDhttps://orcid.org/0000-0001-8074-228X

Biography

I (Bjørn Sand Jensen) am a Lecturer in the Information, Data and Analysis Section in the School of Computing Science, University of Glasgow, working in the interdisciplinary field of probabilistic machine learning, mathematical modeling, interaction and data analysis.

In 2006, I received my Master’s degree in electronic engineering from the Technical University of Denmark, specialising in probabilistic machine learning and signal processing. From 2006-2009 I joined the R&D department of Bang & Olufsen ICEpower.

In 2009, I returned to the Technical University of Denmark to pursue a PhD degree on a fully-funded university stipend under the supervision of Prof Jan Larsen and Prof Lars Kai Hansen. I was awarded the PhD degree in Marts 2013 for my work on preference elicitation and machine learning for integrating subjective and objective observations using Bayesian and non-parametric methods. I continued my research as a Postdoctoral researcher in the Danish strategic research project CoSound, working with several partners from industry, public service and universities (the Royal Library, Denmark's Radio, Bang & Olufsen, Copenhagen University Humanities and Information Science, University of Glasgow, Aalborg University) on large-scale analysis and enrichment of multimedia and cultural heritage archives. I was appointed Lecturer in the School of Computing Science, University of Glasgow in May 2016.

Full CV [pdf] 

ORCID: 0000-0001-8074-228X

Research interests

  • Probabilistic (/Bayesian) machine learning
  • Planning/sequential decision-making under uncertainty (using principles from reinforcement learning, including Bayesian optimisation)
  • Audio processing and modelling
  • Eliciting and modelling human decision-making
  • Bayesian non-parametrics (especially Gaussian processes)
  • Uncertainty quantification in scientific inquiry (e.g. biological image analysis and digital humanities)

 

Publications

List by: Type | Date

Jump to: 2020 | 2019 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2008
Number of items: 25.

2020

Mohammadi, S., Uhrenholt, A. K. and Jensen, B. S. (2020) Odd-One-Out Representation Learning. Object Representations for Learning and Reasoning, 11 Dec 2020. (Accepted for Publication)

Laux, L., Cutiongco, M. F.A. , Gadegaard, N. and Jensen, B. S. (2020) Interactive machine learning for fast and robust cell profiling. PLoS ONE, 15(9), e0237972. (doi: 10.1371/journal.pone.0237972) (PMID:32915784)

Cutiongco, M. F.A. , Jensen, B. S. , Reynolds, P. M. and Gadegaard, N. (2020) Predicting gene expression using morphological cell responses to nanotopography. Nature Communications, 11, 1384. (doi: 10.1038/s41467-020-15114-1)

2019

Tonolini, F., Jensen, B. S. and Murray-Smith, R. (2019) Variational Sparse Coding. In: Conference on Uncertainty in Artificial Intelligence (UAI 2019), Tel Aviv, Israel, 22-25 July 2019,

Uhrenholt, A. K. and Jensen, B. S. (2019) Efficient Bayesian Optimization for Target Vector Estimation. In: The 22nd International Conference on Artificial Intelligence and Statistics, Naha, Okinawa, Japan, 16-18 Apr 2019, pp. 2661-2670.

Sablotny, M., Jensen, B. S. and Johnson, C. W. (2019) Recurrent neural networks for fuzz testing web browsers. In: Lee, K. (ed.) Information Security and Cryptology – ICISC 2018. Series: Lecture Notes in Computer Science (11396). Springer, pp. 354-370. ISBN 9783030121457 (doi:10.1007/978-3-030-12146-4_22)

Uhrenholt, A. and Jensen, B. S. (2019) Efficient Bayesian Optimization for Target Vector Estimation. In: 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), Okinawa, Japan, 16-18 April 2019, pp. 2661-2670.

2015

Madsen, J., Sand Jensen, B. and Larson, J. (2015) Learning Combinations of Multiple Feature Representations for Music Emotion Prediction. In: ASM '15: 1st International Workshop on Affect and Sentiment in Multimedia, Brisbane, Australia, 26-30 Oct 2015, pp. 3-8. ISBN 9781450337502 (doi:10.1145/2813524.2813534)

Sand Jensen, B. , Nielsen, J. B. and Larsen, J. (2015) Perspectives on Bayesian Optimization for HCI. In: CHI 2015: Workshop on Principles, Techniques and Perspectives on Optimization and HCI, Seoul, Republic of Korea, 18-23 Apr 2015,

2014

Madsen, J., Sand Jensen, B. and Larsen, J. (2014) Modeling Temporal Structure in Music for Emotion Prediction using Pairwise Comparisons. In: ISMIR 2014: 15th International Society of Music Information Retrieval Conference, Taipei, Taiwan, 27-31 Oct 2014,

2013

Nielsen, J. B., Sand Jensen, B. , Hansen, T. J. and Larsen, J. (2013) Personalized audio systems - a Bayesian approach. In: 135th International AES Convention, New York City, NY, USA, 17-20 Oct 2013,

Madsen, J., Sand Jensen, B. and Larsen, J. (2013) Predictive modeling of expressed emotions in music using pairwise comparisons. Lecture Notes in Computer Science, 7900, pp. 253-277. (doi: 10.1007/978-3-642-41248-6_14)

Nielsen, J. B., Nielsen, J., Sand Jensen, B. and Larsen, J. (2013) Hearing Aid Personalization. In: 3rd NIPS Workshop on Machine Learning and Interpretation in Neuroimaging 2013, Lake Tahoe, NV, USA, 5-10 Dec 2013,

Sand Jensen, B. , Troelsgaard, R., Larsen, J. and Hansen, L. K. (2013) Towards a universal representation for audio information retrieval and analysis. In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, Vancouver, Canada, 26-31 May 2013, pp. 3168-3172. ISBN 9781479903566 (doi:10.1109/ICASSP.2013.6638242)

Sand Jensen, B. , Nielsen, J. B. and Larsen, J. (2013) Bounded Gaussian Process Regression. In: 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Southampton, UK, 22-25 Sept 2013, pp. 1-6. ISBN 9781479911806 (doi:10.1109/MLSP.2013.6661916)

2012

Alstrøm, T. S., Sand Jensen, B. , Schmidt, M. N., Kostesha, N. V. and Larsen, J. (2012) Haussdorff and hellinger for colorimetric sensor array classification. In: 2012 IEEE International Workshop on Machine Learning for Signal Processing, Santander, Spain, 23-26 Sep 2012, pp. 1-6. ISBN 9781467310246 (doi:10.1109/MLSP.2012.6349724)

Madsen, J., Nielsen, J. B., Sand Jensen, B. and Larsen, J. (2012) Modeling expressed emotions in music using pairwise comparisons. In: 9th International Symposium on Computer Music Modelling and Retrieval (CMMR 2012), London, UK, 19-22 Jun 2012, pp. 526-533.

Madsen, J., Sand Jensen, B. , Larsen, J. and Nielsen, J. B. (2012) Towards predicting expressed emotion in music from pairwise comparisons. In: 9th Sound and Music Computing Conference (SMC 2012), Copenhagen, Denmark, 11-14 Jul 2012, pp. 350-357.

Nielsen, J. B., Sand Jensen, B. and Larsen, J. (2012) Pseudo inputs for pairwise learning with Gaussian processes. In: 2012 IEEE International Workshop on Machine Learning for Signal Processing, Santander, Spain, 23-26 Sep 2012, pp. 1-6. ISBN 9781467310246 (doi:10.1109/MLSP.2012.6349812)

Sand Jensen, B. , Saez Gallego, J. and Larsen, J. (2012) A predictive model of music preference using pairwise comparisons. In: 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, 25-30 Mar 2012, pp. 1977-1980. ISBN 9781467300452 (doi:10.1109/ICASSP.2012.6288294)

2011

Nielsen, J. B., Sand Jensen, B. and Larsen, J. (2011) On sparse multi-task Gaussian process priors for music preference learning. In: 25th Annual Conference on Neural Information Processing Systems : CMPL workshop, Granada, Spain, 12-17 Dec 2011, pp. 1-8.

Sand Jensen, B. , Nielsen, J. B. and Larsen, J. (2011) Efficient preference learning with pairwise continuous observations and Gaussian processes. In: 2011 IEEE International Workshop on Machine Learning for Signal Processing, Santander, Spain, 18-21 Sep 2011, pp. 1-6. ISBN 9781457716218 (doi:10.1109/MLSP.2011.6064616)

2010

Sand Jensen, B. , Larsen, J. E., Jensen, K., Larsen, J. and Hansen, L. K. (2010) Estimating human predictability from mobile sensor data. In: 2010 IEEE International Workshop on Machine Learning for Signal Processing, Kittilä, Finland, 29 Aug - 01 Sep 2010, pp. 196-201. ISBN 9781424478750 (doi:10.1109/MLSP.2010.5588997)

Sand Jensen, B. , Larsen, J., Jensen, K., Larsen, J. E. and Hansen, L. K. (2010) Predictability of mobile phone associations. In: 21st European Conference on Machine Learning : Mining Ubiquitous and Social Environments Workshop, Barcelona, Spain, 20-24 Sep 2010, pp. 91-105.

2008

Tranberg-Hansen, A. S., Madsen, J. and Sand Jensen, B. (2008) A service based estimation method for MPSoC performance modelling. In: Third International Symposium on Industrial Embedded Systems (SIES 2008), Montpellier, France, 11-13 Jun 2008, pp. 43-50. ISBN 9781424419944 (doi:10.1109/SIES.2008.4577679)

This list was generated on Sat Apr 17 20:00:27 2021 BST.
Jump to: Articles | Book Sections | Conference or Workshop Item | Conference Proceedings
Number of items: 25.

Articles

Laux, L., Cutiongco, M. F.A. , Gadegaard, N. and Jensen, B. S. (2020) Interactive machine learning for fast and robust cell profiling. PLoS ONE, 15(9), e0237972. (doi: 10.1371/journal.pone.0237972) (PMID:32915784)

Cutiongco, M. F.A. , Jensen, B. S. , Reynolds, P. M. and Gadegaard, N. (2020) Predicting gene expression using morphological cell responses to nanotopography. Nature Communications, 11, 1384. (doi: 10.1038/s41467-020-15114-1)

Madsen, J., Sand Jensen, B. and Larsen, J. (2013) Predictive modeling of expressed emotions in music using pairwise comparisons. Lecture Notes in Computer Science, 7900, pp. 253-277. (doi: 10.1007/978-3-642-41248-6_14)

Book Sections

Sablotny, M., Jensen, B. S. and Johnson, C. W. (2019) Recurrent neural networks for fuzz testing web browsers. In: Lee, K. (ed.) Information Security and Cryptology – ICISC 2018. Series: Lecture Notes in Computer Science (11396). Springer, pp. 354-370. ISBN 9783030121457 (doi:10.1007/978-3-030-12146-4_22)

Conference or Workshop Item

Mohammadi, S., Uhrenholt, A. K. and Jensen, B. S. (2020) Odd-One-Out Representation Learning. Object Representations for Learning and Reasoning, 11 Dec 2020. (Accepted for Publication)

Conference Proceedings

Tonolini, F., Jensen, B. S. and Murray-Smith, R. (2019) Variational Sparse Coding. In: Conference on Uncertainty in Artificial Intelligence (UAI 2019), Tel Aviv, Israel, 22-25 July 2019,

Uhrenholt, A. K. and Jensen, B. S. (2019) Efficient Bayesian Optimization for Target Vector Estimation. In: The 22nd International Conference on Artificial Intelligence and Statistics, Naha, Okinawa, Japan, 16-18 Apr 2019, pp. 2661-2670.

Uhrenholt, A. and Jensen, B. S. (2019) Efficient Bayesian Optimization for Target Vector Estimation. In: 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), Okinawa, Japan, 16-18 April 2019, pp. 2661-2670.

Madsen, J., Sand Jensen, B. and Larson, J. (2015) Learning Combinations of Multiple Feature Representations for Music Emotion Prediction. In: ASM '15: 1st International Workshop on Affect and Sentiment in Multimedia, Brisbane, Australia, 26-30 Oct 2015, pp. 3-8. ISBN 9781450337502 (doi:10.1145/2813524.2813534)

Sand Jensen, B. , Nielsen, J. B. and Larsen, J. (2015) Perspectives on Bayesian Optimization for HCI. In: CHI 2015: Workshop on Principles, Techniques and Perspectives on Optimization and HCI, Seoul, Republic of Korea, 18-23 Apr 2015,

Madsen, J., Sand Jensen, B. and Larsen, J. (2014) Modeling Temporal Structure in Music for Emotion Prediction using Pairwise Comparisons. In: ISMIR 2014: 15th International Society of Music Information Retrieval Conference, Taipei, Taiwan, 27-31 Oct 2014,

Nielsen, J. B., Sand Jensen, B. , Hansen, T. J. and Larsen, J. (2013) Personalized audio systems - a Bayesian approach. In: 135th International AES Convention, New York City, NY, USA, 17-20 Oct 2013,

Nielsen, J. B., Nielsen, J., Sand Jensen, B. and Larsen, J. (2013) Hearing Aid Personalization. In: 3rd NIPS Workshop on Machine Learning and Interpretation in Neuroimaging 2013, Lake Tahoe, NV, USA, 5-10 Dec 2013,

Sand Jensen, B. , Troelsgaard, R., Larsen, J. and Hansen, L. K. (2013) Towards a universal representation for audio information retrieval and analysis. In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, Vancouver, Canada, 26-31 May 2013, pp. 3168-3172. ISBN 9781479903566 (doi:10.1109/ICASSP.2013.6638242)

Sand Jensen, B. , Nielsen, J. B. and Larsen, J. (2013) Bounded Gaussian Process Regression. In: 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Southampton, UK, 22-25 Sept 2013, pp. 1-6. ISBN 9781479911806 (doi:10.1109/MLSP.2013.6661916)

Alstrøm, T. S., Sand Jensen, B. , Schmidt, M. N., Kostesha, N. V. and Larsen, J. (2012) Haussdorff and hellinger for colorimetric sensor array classification. In: 2012 IEEE International Workshop on Machine Learning for Signal Processing, Santander, Spain, 23-26 Sep 2012, pp. 1-6. ISBN 9781467310246 (doi:10.1109/MLSP.2012.6349724)

Madsen, J., Nielsen, J. B., Sand Jensen, B. and Larsen, J. (2012) Modeling expressed emotions in music using pairwise comparisons. In: 9th International Symposium on Computer Music Modelling and Retrieval (CMMR 2012), London, UK, 19-22 Jun 2012, pp. 526-533.

Madsen, J., Sand Jensen, B. , Larsen, J. and Nielsen, J. B. (2012) Towards predicting expressed emotion in music from pairwise comparisons. In: 9th Sound and Music Computing Conference (SMC 2012), Copenhagen, Denmark, 11-14 Jul 2012, pp. 350-357.

Nielsen, J. B., Sand Jensen, B. and Larsen, J. (2012) Pseudo inputs for pairwise learning with Gaussian processes. In: 2012 IEEE International Workshop on Machine Learning for Signal Processing, Santander, Spain, 23-26 Sep 2012, pp. 1-6. ISBN 9781467310246 (doi:10.1109/MLSP.2012.6349812)

Sand Jensen, B. , Saez Gallego, J. and Larsen, J. (2012) A predictive model of music preference using pairwise comparisons. In: 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, 25-30 Mar 2012, pp. 1977-1980. ISBN 9781467300452 (doi:10.1109/ICASSP.2012.6288294)

Nielsen, J. B., Sand Jensen, B. and Larsen, J. (2011) On sparse multi-task Gaussian process priors for music preference learning. In: 25th Annual Conference on Neural Information Processing Systems : CMPL workshop, Granada, Spain, 12-17 Dec 2011, pp. 1-8.

Sand Jensen, B. , Nielsen, J. B. and Larsen, J. (2011) Efficient preference learning with pairwise continuous observations and Gaussian processes. In: 2011 IEEE International Workshop on Machine Learning for Signal Processing, Santander, Spain, 18-21 Sep 2011, pp. 1-6. ISBN 9781457716218 (doi:10.1109/MLSP.2011.6064616)

Sand Jensen, B. , Larsen, J. E., Jensen, K., Larsen, J. and Hansen, L. K. (2010) Estimating human predictability from mobile sensor data. In: 2010 IEEE International Workshop on Machine Learning for Signal Processing, Kittilä, Finland, 29 Aug - 01 Sep 2010, pp. 196-201. ISBN 9781424478750 (doi:10.1109/MLSP.2010.5588997)

Sand Jensen, B. , Larsen, J., Jensen, K., Larsen, J. E. and Hansen, L. K. (2010) Predictability of mobile phone associations. In: 21st European Conference on Machine Learning : Mining Ubiquitous and Social Environments Workshop, Barcelona, Spain, 20-24 Sep 2010, pp. 91-105.

Tranberg-Hansen, A. S., Madsen, J. and Sand Jensen, B. (2008) A service based estimation method for MPSoC performance modelling. In: Third International Symposium on Industrial Embedded Systems (SIES 2008), Montpellier, France, 11-13 Jun 2008, pp. 43-50. ISBN 9781424419944 (doi:10.1109/SIES.2008.4577679)

This list was generated on Sat Apr 17 20:00:27 2021 BST.

Grants

Current funding:

- KTP (Innovate UK) project, £178k with industry partner Qumodo, Frank Pollick and Paul Siebert.

- CRUK-funded project: A high-content platform for cellular mechanobiology in cancer research (PI: Nikolaj Gadegaard, ~£200k, my ownership 30%).

- EPSRC-funded project: Closed-loop data science (PI: Roderick Murray-Smith,  total ~£3M, my ownership: 4%)) https://www.gla.ac.uk/schools/computing/research/researchsections/ida-section/closedloop/ 

 

 

Supervision

Prospective PhD Students: Feel free to contact me via e-mail or take a look at the School's PGR website .

 

Current postgraduate research students (PhD and MSc by research):

(Anders: Primary, Yanni: Primary (with Ke Yuan); Martin: Primary (with Jeremy Singer), Antanas: Academic supervisor, Andrew: 2nd, Nikolas: 2nd)

Completed postgraduate research projects (PhD and MSc by research):

  • Marie F. Cutiongco, 2019, PhD (co-supervisor, Biomedical engineering, main supervisor: Nikolaj Gadegaard), Correlating single cell form and function under the influence of nanotopography.
  • Jasper Kirton-Wingate, October 2018-2019 (MSc by Research with Widex a/s)
  • Fatma A.I. Elsafoury, 2019, joint supervisor (with Simon Rogers and Chris Claassen), Measuring and Accounting for Spatial and Temporal Trends in Electoral Violence.

Teaching

Standard modules:

  • 2019-2020: Introduction to Data Science and System COMPSCI 5087 (M) (Semester 1), with Dr Jeff Dalton and Dr Nikos Ntarmos.
  • 2019-2020: Artificial Intelligence COMPSCI4004 / COMPCI5987 M/H (Semester 1)
  • 2018-2019: Artificial Intelligence COMPSCI4004 (Semester 2)
  • 2018-2019: Music Curation and Analysis (H) ARTMED4038 (Semester 1, three lectures), with Dr Tim Duguid
  • 2018-2019: Software Engineering (M) COMPSCI5059 (Semester 2), with Dr Ke Yuan
  • 2017-2018: Artificial Intelligence COMPSCI4004 (Semester 1)
  • 2017-2018: Software Engineering (M) COMPSCI5059 (Semester 2), with Dr Ke Yuan
  • 2016-2017: Artificial Intelligence COMPSCI4004 (Semester 1)

 

MSci projects (representative examples):

  • Variational Inference in Bayesian Inverse Reinforcement Learning, P.D., 2018-2019.
  • Machine learning for understanding human decision-making, P.C., 2017-2018.
  • Data-efficient reinforcement learning, G.R., 2017-2018.

 

MSc projects (representative examples):

  • Representation Learning with Sparse VAE for Single-Cell Images, A.R. 2020
  • Tangent propagation for environmental sound classification, B.H., 2020
  • Accelerating Image-Based Cell Profiling with Machine Learning, L.L, 2018 [best project award]
  • Perceptual Embeddings of Music Objects using Machine Learning, H. W., 2017
  • A toolbox for performance modelling and selection of dense neural network architectures, F. B., 2017

 

Honors projects (i.e. final year projects - representative examples)

  • Preference Elicitation for Music using Spoken Dialogue Systems, M.B, 2017-2018.
  • Hybrid Music Recommendation, A.G., 2017-2018
  • Interactive Machine Learning for Time Series Prediction, B.A., 2017-2018
  • Neural Networks for Dialogue Systems, Z.I, 2017-2018

 

Summer internships (representative examples):

  • Generative modelling and representation learning for audio, S.M., Summer 2019 (funded by SoCS)
  • Deep Learning for Image Analysis of Biological Cells, M.D., 2017

Additional information

Local activities (UofG)

  • 2016- : Member of the Research Student Committee in the School of Computing Science.

 

Reviewer / programme committee:

  • I am a recurrent reviewer for NeurIPS (formerly NIPS), AISTATS, ICML, ICLR, UAI, MLSP, ICASSP, ICMI, IEEE Affective Computing.