Dr Bjorn Jensen
- Lecturer in Computing Science (Computing Science)
telephone: 0141 330 1639
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 working on perceptual audio signal processing while also representing the company in the DANES research project as steering group member.
In 2009, I returned to the Technical University of Denmark to pursue a PhD degree on a fully funded university stipend under the supervision Prof Jan Larsen and co-supervised by 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, Glasgow University, 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]
- 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)
- The role of uncertainty quantification in scientific inquiry (e.g. biological image analysis and digital humanities)
- Co-investigator in the CRUK-funded project: A high-content platform for cellular mechanobiology in cancer research (PI: Nikolaj Gadegaard, ~£200k, my ownership 30%).
- Co-investigator in the 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/
- PhD studentship funded by Widex a/s: Data-driven hearing aid solutions, 2018-2021, part of the closed-loop data science project).
- Anders Kirk Uhrenholt (main supervisor)
- NN, October 2018-2021, with Widex a/s
- NN, Sep 2018- (EngD with Canon medical research and the EPSRC Centre for Doctoral Training in Applied Photonics)
- Marie F. Cutiongco (co-supervisor, Biomedical engineering, Main supervisor: Nikolaj Gadegaard), The dynamic nature of focal adhesions on nanotopographies
- Fatma A.I. Elsafoury (supervisor), Measuring and Accounting for Spatial and Temporal Trends in Electoral Violence
- Marco Cook (2nd supervisor), SCADA Cybersecurity in Factories of the Future
- Fyfe, Andrew
Adaptive Tools in Immersive Digital Music Performance
- Sablotny, Martin
The Application of Machine Learning to Cyber Defence In Critical Applications
Prospective PhD Students: Please have a look at the School's PGR website before contacting me via e-mail. Feel free to contact any of my current or past students to learn about my approach to supervision).
Current PhD Students (main and co-supervisor):
(Anders: Main, Martin: Co-supervisor, Marie: Co-supervisor, Fatma: Supervisor, Marco: 2nd)
- 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):
- Machine learning for understanding human decision-making, P.C., 2017-2018
- Data-efficient reinforcement learning, G.R., 2017-2018
- Machine learning for metal detection L.T, 2017-2018
MSc projects (representative examples):
- 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):
- Deep Learning for Image Analysis of Biological Cells, M.D., 2017
Local activities (UofG)
- 2016- : Member of the Research Student Committee in the School of Computing Science
Reviewer / programme committee:
- I am currently a reviewer for NeuIPS (formerly NIPS), AISTATS, ICML, ICLR, MLSP, ICASSP
- I have in the past reviewed for ICMI, IEEE Affective Computing,...