Dr. Pedram Ghamisi

Tel:   +49 (0)8153 28 4296
Fax:  +49 (0)8153 28 1420
Room: 1022 (DLR-EOC)
E-mail: pedram.ghamisi@dlr.de
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Curriculum Vitae

Pedram Ghamisi graduated with a B.Sc. in civil (survey) engineering from the Tehran South Campus of Azad University. Then, he obtained an M.Sc. degree with first class honors in remote sensing at K. N. Toosi University of Technology in 2012. He received a Ph.D. in electrical and computer engineering at the University of Iceland, Reykjavik, Iceland in 2015. In the academic year 2010-2011, he received the Best Researcher Award for M.Sc. students in K. N. Toosi University of Technology. At the 2013 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Melbourne, July 2013, Dr. Ghamisi was awarded the IEEE Mikio Takagi Prize for winning the Student Paper Competition at the conference among almost 70 people. Then, he worked as a postdoctoral research fellow at the University of Iceland. In 2015, Dr. Ghamisi won the prestigious Alexander von Humboldt Fellowship and started his work as a postdoctoral research fellow at Technische Universität München (TUM), Signal Processing in Earth Observation, Munich, Germany from October, 2015. He has also been working as a researcher at German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Germany since October, 2015. His research interests are in remote sensing and image analysis with a special focus on spectral and spatial techniques for hyperspectral image classification and the integration of LiDAR and hyperspectral data for land cover assessment. For more information, please check my website: http://pedram-ghamisi.com/



  • The recipient of the IEEE Mikio Takagi Prize which was awarded for the rst place in the Student Paper Competition at the 2013 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Melbourne, July 2013.

  • Best Researcher Award for students in K. N. Toosi University of Technology in academic year: 2010-2011.

  • First Class Honours in MSc
  • Alexander von Humboldt Fellowship for postdoctoral researcher.

  • Australia Research Scholarship, International Postgraduate Research Scholarship (IPRS)

  • Fellowship awarded by The Icelandic Centre for Research (Rannis)

Editorial Activities

  • IEEE Geoscience and Remote Sensing Letter (GRSL)

  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sens-
    ing (JSTARS)

  • IEEE Trans. on Geoscience and Remote Sensing (TGRS)

  • IEEE Trans. on Image Processing

  • Pattern Recognition Letter

  • Remote Sensing (MDPI)

  • Canadian Journal of Remote Sensing (CJRS)

  • Journal of Applied Remote Sensing (JARS)

  • Neural Computing and Applications

  • WHISPERS 2013, 2014

  • 11th International Workshop, MCS 2013 Nanjing, China

  •  .....

Reseach Interests

  • Image and signal processing for earth observation
  • Hyperspectral image analysis
  • Spectral-spatial classification of hyperspectral data
  • Feature extraction and selection
  • Fusion of LiDAR and hyperspectral data
  • Deep learning

Key Publications

  • (Book) J. A. Benediktsson and P. Ghamisi, Spectral-Spatial Classi cation of Hyperspectral Remote Sensing Images, Artech House Publishers, INC, Boston, USA, 2015.

  • (Book) M. S. Couceiro and P. Ghamisi, Fractional Order Darwinian Particle Swarm Optimization: Applications and Evaluation of an Evolutionary Algorithm, Springer, London, UK, 2015.

  • P. Ghamisi, M. S. Couceiro, J. A. Benediktsson and N. M. F. Ferreira, "An Efficient Method for Segmentation of Images Based on Fractional Calculus and Natural Selection," Expert Systems With Applications, vol. 39, no. 16, pp. 12407-12417, Nov. 2012.

  • P. Ghamisi, J. A. Benediktsson and M. O. Ulfarsson, "Spectral-Spatial Classi fication of Hyperspectral Images Based on Hidden Markov Random Fields," IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 5, pp. 2565-2574, May 2014.

  • P. Ghamisi, M. Dalla Mura and J. A. Benediktsson, "A Survey on Spectral-Spatial Classi cation Techniques Based on Attribute Pro les," IEEE Transactions
    on Geoscience and Remote Sensing, vol. 53, no. 5, pp. 2335-2353, May 2015.