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Fredrik Sandin
Fredrik Sandin

Fredrik Sandin

Luleå University of Technology
Machine Learning
Embedded Intelligent Systems LAB
Department of Computer Science, Electrical and Space Engineering
+46 (0)920 493163
A2304 Luleå


Brain-inspired machine learning and neuromorphic computing. See my scholar profile or scopus profile for references.

NCE focus issue: applications of neuromorphic engineering to wireless networks for distributed sensing .

SAIS21 in Luleå,


I have a PhD in Physics (2007, Swedish Graduate School of Space Technology) and I did a postdoc at IFPA in Belgium (2008-09), both focusing on numerical simulations and modeling in theoretical physics. I did the MSc diploma work in ATLAS at CERN (2001). My curiosity for brains, neuromorphic engineering and the physics of brains made me shift research focus. I did a second postdoc in brain-inspired machine learning (2010-11) at EISLAB, where I presently work.


I am the examiner of the following courses:

  • Neural networks and learning machines (D7046E), link .
  • Neuromorphic computing, upcoming course in the Applied AI program.

Since 2014, I coordinate the "Technical Physics and Electrical Engineering" program at LTU (Master of Science, 300Hp). In the past I was the examiner for E0003E Electric circuit theory, D0011E Digital design, D0017E Introduction to programming for engineers. Before 2010 I taught several courses in physics.


Current PhD students

Past Postdocs

Graduated PhD students

  • Siddharth Dadhich, Automation of Wheel-Loaders, link (co-supervisor).
  • Sergio Martin del Campo Barraza, Unsupervised feature learning applied to condition monitoring, link .
  • Blerim Emruli, Ubiquitous Cognitive Computing: A Vector Symbolic Approach, link .


Some code and tools. Contact me if you are interested in code used in research articles that is not listed below.

  • 3FCS code, link .This code was developed and used for the quark matter calculations in the papers about neutron stars with quark matter cores and related phase diagrams, including my most cited paper in Phys. Reef. D.
  • Femtolensing tool, link . Calculates the gravitational lensing signatures of low-mass (10 14 -10 17 kg) compact interstellar objects. This code was developed when working on the preon star hypothesis, see highlights below.
  • N-dimensional random projection code, link . Result of early work on representation learning for cognitive computing.
  • CBVS code, link . Early work on cognitive computing.
  • Dircheck, link . A useful tool for verification of file archives.
  • Python code for distributed computing over ssh, link .
  • ASOUND Matlab plugin, link .
  • Online collaborative writing in Latex, link . Developed before the time of Sharelatex / Overleaf etc.

Some highlights


Article in journal

Algorithmic performance constraints for wind turbine condition monitoring via convolutional sparse coding with dictionary learning (2021)

Martin-del-Campo. S, Sandin. F, Schnabel. S
Journal of Risk and Reliability, Vol. 235, nr. 4, s. 660-675
Article in journal

Dictionary Learning Approach to Monitoring of Wind Turbine Drivetrain Bearings (2021)

Martin-del-Campo. S, Sandin. F, Strömbergsson. D
International Journal of Computational Intelligence Systems, Vol. 14, nr. 1, s. 106-121
Conference paper

Pretraining Image Encoders without Reconstruction via Feature Prediction Loss (2021)

Grund Pihlgren. G, Sandin. F, Liwicki. M
Part of: Proceedings of ICPR 2020, 25th International Conference on Pattern Recognition, s. 4105-4111, IEEE, 2021
Conference paper

Adaptation of a wheel loader automatic bucket filling neural network using reinforcement learning (2020)

Dadhich. S, Sandin. F, Bodin. U, Andersson. U, Martinsson. T
Part of: 2020 International Joint Conference on Neural Networks (IJCNN), IEEE, 2020, 20563
Conference paper

Autoencoder Alignment Approach to Run-Time Interoperability for System of Systems Engineering (2020)

Nilsson. J, Delsing. J, Sandin. F
Part of: IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings, s. 139-144, IEEE, 2020