World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
6256
World Ranking
13892
National Ranking
108

Overview

Joakim Jalden is affiliated with the Royal Institute of Technology in Sweden. Their research spans multiple fields, primarily in Engineering and Biochemistry, Genetics and Molecular Biology.

Their work covers diverse subfields including Electrical and Electronic Engineering, Molecular Biology, Artificial Intelligence, Biomedical Engineering, and Aerospace Engineering. Jalden's contributions are particularly notable in the following main research topics:

  • Nanopore and Nanochannel Transport Studies
  • Advanced MIMO Systems Optimization
  • Genomics and Phylogenetic Studies
  • Millimeter-Wave Propagation and Modeling
  • COVID-19 Epidemiological Studies
  • Sparse and Compressive Sensing Techniques
  • Direction-of-Arrival Estimation Techniques

Jalden has published extensively in venues such as:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Sensors Journal
  • IEEE Transactions on Signal Processing

Their recent papers include:

  • The effect of interventions on COVID-19, 2020, Nature
  • Matrix-Inverse-Free Deep Unfolding of the Weighted MMSE Beamforming Algorithm, 2021, IEEE Open Journal of the Communications Society
  • Self-Calibration of Inertial Sensor Arrays, 2021, IEEE Sensors Journal
  • A Geometrically Converging Dual Method for Distributed Optimization Over Time-Varying Graphs, 2020, IEEE Transactions on Automatic Control
  • A Matrix-Inverse-Free Implementation of the MU-MIMO WMMSE Beamforming Algorithm, 2022, IEEE Transactions on Signal Processing

Frequent coauthors include Javier Kipen, Xuechun Xu, Lissy Pellaco, Yasaman Khorsandmanesh, and Emil Björnson. The collaborative relationship with these colleagues is reflected in multiple joint publications, with collaborations ranging from five to eight instances each.

Best Publications

  • Objective comparison of particle tracking methods

    Nicolas Chenouard;Ihor Smal;Fabrice de Chaumont;Martin Maška;Martin Maška

  • On the complexity of sphere decoding in digital communications

    J. Jalden;B. Ottersten

  • An objective comparison of cell-tracking algorithms

    Vladimír Ulman;Martin Maška;Klas E G Magnusson;Olaf Ronneberger

  • A benchmark for comparison of cell tracking algorithms

    Martin Maška;Vladimír Ulman;David Svoboda;Pavel Matula

  • Lattice Reduction

    Dirk Wübben;Dominik Seethaler;Joakim Jaldén;Gerald Matz

  • Global Linking of Cell Tracks Using the Viterbi Algorithm

    Klas E. G. Magnusson;Joakim Jalden;Penney M. Gilbert;Helen M. Blau

  • Lattice Reduction

    Unknown

  • On using an adaptive neural network to predict lung tumor motion during respiration for radiotherapy applications.

    Marcus Isaksson;Joakim Jalden;Martin J. Murphy

  • Fixed-Complexity Soft MIMO Detection via Partial Marginalization

    E.G. Larsson;J. Jalden

  • Worst- and average-case complexity of LLL lattice reduction in MIMO wireless systems

    J. Jalden;D. Seethaler;G. Matz

  • DMT Optimality of LR-Aided Linear Decoders for a General Class of Channels, Lattice Designs, and System Models

    Joakim Jaldén;Petros Elia

  • The Error Probability of the Fixed-Complexity Sphere Decoder

    J. Jalden;L.G. Barbero;B. Ottersten;J.S. Thompson

  • Semidefinite programming for detection in linear systems - optimality conditions and space-time decoding

    J. Jalden;C. Martin;B. Ottersten

  • An exponential lower bound on the expected complexity of sphere decoding

    J. Jalden;B. Ottersten

  • Parallel Implementation of a Soft Output Sphere Decoder

    J. Jalden;B. Ottersten

  • Adaptive filtering to predict lung tumor motion during free breathing

    Martin J. Murphy;Marcus Isaakson;Joakim Jalden

  • Optimal UAV Base Station Trajectories Using Flow-Level Models for Reinforcement Learning

    Vidit Saxena;Joakim Jalden;Henrik Klessig

  • The Diversity Order of the Semidefinite Relaxation Detector

    J. Jalden;B. Ottersten

  • Vector Perturbation Precoding Revisited

    J Maurer;Joakim Jaldén;D Seethaler;G Matz

  • The Equivalence of Semidefinite Relaxation MIMO Detectors for Higher-Order QAM

    Wing-Kin Ma;Chao-Cheng Su;J. Jalden;Tsung-Hui Chang

  • A batch algorithm using iterative application of the Viterbi algorithm to track cells and construct cell lineages

    Klas E. G. Magnusson;Joakim Jalden

Frequent Co-Authors

Bjorn Ottersten
Bjorn Ottersten University of Luxembourg
Mats Bengtsson
Mats Bengtsson Royal Institute of Technology
Peter Händel
Peter Händel Royal Institute of Technology
Fredrik Gustafsson
Fredrik Gustafsson Linköping University
Thomas B. Schön
Thomas B. Schön Uppsala University
Isaac Skog
Isaac Skog Royal Institute of Technology
Wing-Kin Ma
Wing-Kin Ma Chinese University of Hong Kong
James Gross
James Gross Royal Institute of Technology
Helen M. Blau
Helen M. Blau Stanford University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA opens up several flexible online education options. Aspiring professionals can start with 2 year online degrees, which provide foundational skills for entry-level tech jobs or further study.

For those looking to quickly boost their credentials, consider easy certifications to get online. These programs are efficient, often completed in months, and cover in-demand fields like cybersecurity or networking.

Many working professionals prefer to accelerate their education with the shortest masters degree options. These intensive online programs can be finished in as little as one year, allowing quicker entry or advancement in the job market.

When planning long-term, it’s wise to review which master's degree is most in demand in usa. Choosing a degree that aligns with hiring trends increases career prospects and salary potential.

Whether you are just starting or looking to specialize, these online programs offer flexible and valuable pathways to high-growth tech careers.

Best Scientists Citing Joakim Jalden

Trending Scientists

Recently Published Articles