Johan Karlsson, PhD
Professor, Department of Mathematics
Associate Director Executive Research,
Digital Futures
KTH, Royal Institute of Technology

Johan Karlsson received an MSc degree in Engineering Physics from KTH in 2003 and a PhD in Optimization and Systems Theory from KTH in 2008. From 2009 to 2011, he was with Sirius International, Stockholm. From 2011 to 2013 he was working as a postdoctoral associate at the Department of Computer and Electrical Engineering, University of Florida. From 2013 he joined the Department of Mathematics, KTH, and since 2023 he is working as an professor. His current research interests include inverse problems, methods for large scale optimization, and model reduction, for applications in remote sensing, signal processing, and control theory.

Phone: +46-(0)8-790 8440
Mail: johan.karlsson at math.kth.se


Workshops and conferences

Previous workshops:


Teaching and student projects

Courses:

Previous Courses:

Master thesis projects:

Some tips and guidelines for thesis work.

Research Group

Current PhD students:

  1. Martin Ryner. Industrial PhD student, Vironova.
  2. Michele Mascherpa.
  3. Linn Engström. Main supervisor: Sigrid Källblad.
  4. Martin Tronstad. Main supervisor: Joakim Dahlin, KI.

Former PhD students:

  1. Isabel Haasler. Currently postdoc at EPFL.
  2. Silun Zhang. Main supervisor: Xiaoming Hu. Silun is currently Assistant professor at KTH.
  3. Emil Ringh. Main Supervisor: Elias Jarlebring. Emil is currently with Ericsson Research.
  4. Axel Ringh. Currenlty assistant professor at Chalmers University of Technology.

Publications

Journal papers:

  1. G. Fanizza, J. Karlsson, A. Lindquist, and R. Nagamune: Passivity-preserving model reduction by analytic interpolation.
    Journal of linear algebra and its applications, vol. 425, pp. 608-633, September 2007.
  2. J. Karlsson and A. Lindquist: Stability-preserving rational approximation subject to interpolation constraints.
    IEEE Transactions on Automatic Control, vol. 53, pp. 1724-1730, August 2008. Full length version.
  3. T. Georgiou, J. Karlsson, and S. Takyar: Metrics for power spectra: an axiomatic approach.
    IEEE Transactions on Signal Processing, vol. 57, pp. 859-867, March 2009.
  4. J. Karlsson and A. Lindquist: On complexity constrained interpolation with interpolation points close to the boundary.
    IEEE Transactions on Automatic Control, vol. 54, pp. 1412-1418, June 2009.
  5. J. Karlsson, T. Georgiou, and A. Lindquist: The inverse problem of analytic interpolation with degree constraint and weight selection for control synthesis.
    IEEE Transactions on Automatic Control, vol. 55, pp. 405-418, February 2010.
  6. O. Ojowu Jr., J. Karlsson, J. Li, and Y. Liu: ENF extraction from digital recordings using adaptive techniques and frequency tracking.
    IEEE Transactions on Information Forensics & Security, vol. 7, pp. 1330-1338, August 2012.
  7. J. Karlsson and T. Georgiou: Uncertainty bounds for spectral estimation.
    IEEE Transactions on Automatic Control, vol 58, pp. 1659-1673, July 2013.
  8. K. Zhao, J. Liang, J. Karlsson, and J. Li: Enhanced multistatic active sonar signal processing.
    Journal of the Acoustical Society of America, vol. 134, pp. 300-311, July 2013.
  9. J. Karlsson, W. Rowe, L. Xu, G-O. Glentis, and J. Li: Fast missing data IAA with application to notched spectrum SAR.
    IEEE Transactions on Aerospace and Electronic Systems, vol. 50, pp. 959-971, July 2014.
  10. J. Karlsson, A. Lindquist, and A. Ringh: The multidimensional moment problem with complexity constraint.
    Integral Equations and Operator Theory, vol. 84, issue 3, pp. 395-418, March 2016.
  11. A. Ringh, J. Karlsson, and A. Lindquist: Multidimensional rational covariance extension with applications to spectral estimation and image compression.
    SIAM Journal on Control and Optimization, vol. 54, no. 4, pp. 1950-1982, 2016.
  12. J. Karlsson, A. Ringh: Generalized Sinkhorn iterations for regularizing inverse problems using optimal mass transport.
    SIAM Journal on Imaging Sciences, vol 10, no 4, pp. 1935-1962, 2017.
  13. Y. Chen, J. Karlsson, and T.T. Georgiou: The role of the time-arrow in mean-square estimation of stochastic processes.
    IEEE Control Systems Letters, vol 2, no 1, pp. 85-90, 2018
  14. E. Ringh, G. Mele, J. Karlsson, E. Jarlebring: Sylvester-based preconditioning for the waveguide eigenvalue problem.
    Linear Algebra and its Applications, vol 542, pp. 441-463, April 2018.
  15. A. Ringh, J. Karlsson, and A. Lindquist: Multidimensional rational covariance extension with approximate covariance matching.
    SIAM Journal on Control and Optimization, vol 56, Issue 2, pp. 913-944, 2018.
  16. Y. Chen and J. Karlsson: State tracking of linear ensembles via optimal mass transport.
    IEEE Control Systems Letters, vol 2, no 2, pp. 260-265, 2018.
  17. F. Elvander, A. Jakobsson, and J. Karlsson: Interpolation and Extrapolation of Toeplitz Matrices via Optimal Mass Transport.
    IEEE Transactions on Signal Processing, vol 66, no 20, pp. 5385-5398, 2018.
  18. S. Banert, A. Ringh, J. Adler, J. Karlsson, O. Öktem: Data-driven nonsmooth optimization
    SIAM Journal on Optimization, vol 30, issue 1, pp. 102-131, 2020.
  19. F. Elvander, I, Haasler, A. Jakobsson, and J. Karlsson: Multi-Marginal Optimal Transport using Partial Information with Applications in Robust Localization and Sensor Fusion.
    Signal Processing, available online (107474), 11 January, 2020.
  20. S. Zhang, A. Ringh, X. Hu, and J. Karlsson: Modeling collective behaviors: A moment-based approach.
    IEEE Transactions on Automatic Control. Published online: 26 February 2020.
  21. R. Singh, I. Haasler, Q. Zhang, J. Karlsson, Y. Chen: Incremental inference of collective graphical models.
    IEEE Control Systems Letters, vol 5, no 2, pp. 421-426, 2020.
  22. I. Haasler, Y. Chen, and J. Karlsson: Optimal Steering of Ensembles With Origin-Destination Constraints.
    IEEE Control Systems Letters, vol 5, no 3, pp. 881-886, 2020.
  23. B. Zhu, A. Ferrante, J. Karlsson, M. Zorzi: M^2-Spectral Estimation: A Relative Entropy Approach.
    Automatica, Vol 125, March 2021
  24. I. Haasler, R. Singh, Q. Zhang, J. Karlsson, and Y. Chen: Multi-marginal optimal transport and probabilistic graphical models.
    IEEE Transactions on Information Theory, vol 67, no 7, July 2021.
  25. I. Haasler, J. Karlsson, and A. Ringh: Control and estimation of ensembles via structured optimal transport, A computational approach based on entropy-regularized multi-marginal optimal transport.
    IEEE Control Systems Magazine 41 (4), 50-69, 2021.
  26. I. Haasler, A. Ringh, Y. Chen, J. Karlsson: Multi-marginal optimal transport with a tree-structured cost and the Schroedinger bridge problem.
    SIAM Journal on Control and Optimization, 59(4), 2428-2453, 2021.
  27. B. Zhu, A. Ferrante, J. Karlsson, M. Zorzi: M^2-Spectral Estimation: A Flexible Approach Ensuring Rational Solutions.
    SIAM Journal on Control and Optimization, 59(4), 2977-2996, 2021.
  28. A. Ringh, J. Karlsson, and A. Lindquist: An analytic interpolation approach to stability margins with emphasis on time delay.
    IEEE Transactions on Automatic Control, vol: 67, Issue: 1, January 2022.
  29. R. Singh, I. Haasler, Q. Zhang, J. Karlsson, Y. Chen: Inference with Aggregate Data: An Optimal Transport Approach.
    IEEE Transactions on Automatic Control, vol: 67, Issue: 9, September 2022.
  30. F. Elvander, J. Karlsson: Variance Analysis of Covariance and Spectral Estimates for Mixed-Spectrum Continuous-Time Signals.
    IEEE Transactions on Signal Processing, vol: 71, 1395 - 1407, April 2023.
  31. I. Haasler, A. Ringh, Y. Chen, J. Karlsson: Scalable computation of dynamic flow problems via multi-marginal graph-structured optimal transport.
    Mathematics of Operations Research, 2023.
  32. M. Mascherpa, I. Haasler, B. Ahlgren, J. Karlsson: Estimating pollution spread in water networks as a Schrödinger bridge problem with partial information.
    European Journal of Control, 100846, Available online 16 June 2023,
  33. A Ringh, I Haasler, Y Chen, J Karlsson: Mean field type control with species dependent dynamics via structured tensor optimization.
    IEEE Control Systems Letters, 2023.

Preprints:

  1. A. Ringh, I. Haasler, Y. Chen, and J. Karlsson: Graph-structured tensor optimization for nonlinear density control and mean field games.
  2. M. Ryner, J. Karlsson: Orthogonalization of data via Gromov-Wasserstein type feedback for clustering and visualization.

Conference papers (peer-reviewed):

  1. J. Karlsson and T. Georgiou: Signal analysis, moment problems & uncertainty measures.
    IEEE Conference on Decision and Control, and IEEE European Control Conference, 2005.
  2. J. Karlsson and A. Lindquist: On complexity constrained interpolation with interpolation points close to the boundary.
    International Symposium on the Mathematical Theory of Networks and Systems, 2006.
  3. G. Fanniza, J. Karlsson, A. Lindquist, and R. Nagamune: A global analysis approach to passivity preserving model reduction.
    IEEE Conference on Decision and Control, 2006.
  4. J. Karlsson, T. Georgiou, and A. Lindquist: The inverse problem of analytic interpolation with degree constraint.
    IEEE Conference on Decision and Control, 2006.
  5. J. Karlsson and A. Lindquist: Stable rational approximation in the context of interpolation and convex optimization.
    IEEE Conference on Decision and Control, 2007.
  6. X. Jiang, J. Karlsson, and T. Georgiou: Phoneme segmentation based on spectral metrics.
    International Symposium on the Mathematical Theory of Networks and Systems, 2008.
  7. P. Enqvist and J. Karlsson: Minimal Itakura-Saito distance and covariance interpolation.
    International Symposium on the Mathematical Theory of Networks and Systems, 2008.
  8. J. Karlsson, T. Georgiou, and A. Lindquist: Weight selection for control synthesis with degree-constrained controllers.
    International Symposium on the Mathematical Theory of Networks and Systems, 2008.
  9. P. Enqvist and J. Karlsson: Minimal Itakura-Saito distance and covariance interpolation.
    IEEE Conference on Decision and Control, 2008.
  10. J. Karlsson, S. Takyar, and T. Georgiou: Transport metrics for power spectra.
    IEEE Conference on Decision and Control, 2008.
  11. J. Karlsson, T. Georgiou, and A. Lindquist: Weight selection for gap robustness with degree-constrained controllers.
    IEEE Conference on Decision and Control, 2008.
  12. W. Rowe, J. Karlsson, L. Xu, and J. Li: Untangling multipath returns in MIMO radar via waveform diversity.
    IEEE Sensor Array and Multichannel Signal Processing Workshop, 2012.
  13. J. Karlsson and P. Enqvist: Input-to-state covariances for spectral analysis: The biased estimate.
    International Symposium on the Mathematical Theory of Networks and Systems, 2012.
  14. J. Karlsson and T. Georgiou: Metric uncertainty for spectral estimation based on Nevanlinna-Pick interpolation.
    International Symposium on the Mathematical Theory of Networks and Systems, 2012.
  15. W. Rowe, J. Karlsson. Xu, G. Glentis, and J. Li: SAR imaging in the presence of spectrum notches via fast missing data IAA.
    SPIE Defense, Security, and Sensing, 2013.
  16. K. Zhao, J. Liang, J. Karlsson, and J. Li: Enhanced multistatic active sonar signal processing.
    IEEE International Conference on Acoustics, Speech, and Signal Processing, 2013.
  17. J. Karlsson, W. Rowe, L. Xu, G. Glentis, and J. Li: Fast missing data IAA by low rank completion.
    IEEE International Conference on Acoustics, Speech, and Signal Processing, 2013.
  18. W. Rowe, J. Karlsson, and J. Li: Error analysis of MIMO monopulse for tracking radar.
    International Radar Symposium, 2013.
  19. J. Karlsson, J. Li, and P. Stoica: Filter design with hard spectral constraints.
    European Signal Processing Conference, 2014.
  20. G.O. Glentis, J. Karlsson, A. Jakobsson, and J. Li: Efficient spectral analysis in the missing data case using sparse ML methods.
    European Signal Processing Conference, 2014.
  21. J. Karlsson and L. Ning: On robustness of L1-regularization methods for spectral estimation. Presentation.
    IEEE Conference on Decision and Control, 2014.
  22. A. Sadeghian D. Lim, J. Karlsson, and J. Li: Automatic target recognition using discrimination based on optimal transport.
    IEEE International Conference on Acoustics, Speech, and Signal Processing, 2015.
  23. A. Ringh and J. Karlsson: A fast solver for the circulant rational covariance extension problem.
    IEEE European Control Conference, 2015.
  24. A. Gattami, E. Ringh, and J. Karlsson: Time localization and capacity of faster-than-Nyquist signaling.
    IEEE Globecom, 2015.
  25. A. Ringh, J. Karlsson, and A. Lindquist: The multidimensional circulant rational covariance extension problem: solutions and applications in image compression.
    IEEE Conference on Decision and Control, 2015.
  26. J. Karlsson, P. Enqvist, and A. Gattami: Confidence Assessment for Spectral Estimation based on Estimated Covariances.
    IEEE International Conference on Acoustics, Speech, and Signal Processing, 2016.
  27. F. Elvander, S. Adalbjörnsson, J. Karlsson, and A. Jakobsson: Using optimal transport for estimating inharmonic pitch signals.
    IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017.
  28. J. Adler, A. Ringh, O. Öktem, J. Karlsson: Learning to solve inverse problems using Wasserstein loss
    NIPS, Optimal Transport & Machine Learning workshop, 2017.
  29. A. Ringh, J. Karlsson, and A. Lindquist: Further results on multidimensional rational covariance extension with application to texture generation.
    IEEE Conference on Decision and Control, 2017.
  30. F. Elvander, A. Jakobsson, and J. Karlsson: Using Optimal Mass Transport for Tracking and Interpolation of Toeplitz Covariance Matrices.
    IEEE International Conference on Acoustics, Speech, and Signal Processing, 2018.
  31. F. Elvander, I. Haasler, A. Jakobsson, and J. Karlsson: Tracking and Sensor Fusion in Direction of Arrival Estimation Using Optimal Mass Transport.
    European Signal Processing Conference, 2018.
  32. A. Ringh, J. Karlsson, and A. Lindquist: Lower bounds on the maximum delay margin by analytic interpolation.
    IEEE Conference on Decision and Control, 2018.
  33. S. Zhang, A. Ringh, X. Hu, and J. Karlsson: A moment-based approach to modeling collective behaviors.
    IEEE Conference on Decision and Control, 2018.
  34. F. Elvander, I. Haasler, A. Jakobsson, and J. Karlsson: Non-coherent sensor fusion via entropy regularized optimal mass transport.
    IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019.
  35. I. Haasler, A. Ringh, Y. Chen, and J. Karlsson: Estimating ensemble flows on a hidden Markov chain.
    IEEE Conference on Decision and Control, 2019.
  36. B. Zhu, A. Ferrante, J. Karlsson, M. Zorzi: Fusion of Sensors Data in Automotive Radar Systems: a Spectral Estimation Approach.
    IEEE Conference on Decision and Control, 2019.
  37. F. Elvander, J. Karlsson, T. van Waterschoot: Convex Clustering for Multistatic Active Sensing via Optimal Mass Transport.
    European Signal Processing Conference (EUSIPCO), 1730-1734, 2021.
  38. A. Ringh, J. Karlsson, A. Lindquist: On analytic interpolation with non-classical constraints for solving problems in robust control.
    American Control Conference (ACC), 2374-2381, 2021.
  39. I. Haasler, A. Ringh, Y. Chen, and J. Karlsson: Efficient computations of multi-species mean field games via graph-structured optimal transport.
    IEEE Conference on Decision and Control, 2021.
  40. J. Fan, I. Haasler, J. Karlsson, and Y. Chen: On the complexity of the optimal transport problem with graph-structured cost.
    AISTATS, 2022.
  41. F. Elvander, J. Karlsson, T. van Waterschoot: Worst-case uncertainty bounds in covaraiance interpolation..
    European Signal Processing Conference (EUSIPCO), 1730-1734, 2022.
  42. M. Ryner, J. Kronqvist, J. Karlsson: Globally solving the Gromov-Wasserstein problem for point clouds in low dimensional Euclidean spaces.
    NeurIPS 2023.

Extended abstracts (peer-reviewed):

  1. Y. Chen, J. Karlsson, and T. Georgiou: The role of past and future in estimation and the reversibility of stochastic processes.
    International Symposium on the Mathematical Theory of Networks and Systems, 2014.
  2. A. Ringh, J. Karlsson, and A. Lindquist: Multidimensional Rational Covariance Extension with Approximate Covariance Matching.
    International Symposium on the Mathematical Theory of Networks and Systems, 2016.
  3. J. Karlsson and L. Ning: Super-Resolution methods and Metric Uncertainty via Optimal Transport. Presentation.
    International Symposium on the Mathematical Theory of Networks and Systems, 2016.
  4. Y. Chen and J. Karlsson: Tracking distributions of linear dynamical systems: an optimal mass transport approach.
    International Symposium on the Mathematical Theory of Networks and Systems, 2018.
  5. J. Karlsson, A. Ringh: Optimal mass transport for regularizing inverse problems using generalized Sinkhorn iterations.
    International Symposium on the Mathematical Theory of Networks and Systems, 2018.
  6. S. Zhang, A. Ringh, X. Hu, and J. Karlsson: Modeling collective behaviors: A moment-based approach.
    International Symposium on the Mathematical Theory of Networks and Systems, 2018.

Theses: