Abbas Cheddad

Abbas Cheddad


DIDA, Rum J3112


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Short Biography

I did my PhD at the faculty of Computing and Engineering at the University of Ulster in Northern Ireland, UK. I worked as a post-doc at Umeå University (Sweden) and also was affiliated with the Karolinska Institute in Stockholm for several years. From Oct 2015, I joined the Blekinge Institute of Technology in Karlskrona (Sweden) as a senior lecturer (Dpt of Computer Science and Engineering) where I hold, currently, the title of  Associate Professor (Docent). Alongside my teaching duties, I am participating in a large research project, “Scalable resource-efficient systems for big data analytics,” where close research collaboration with industry is key for the project execution. I invest my expertise in image processing into this project that focuses on Big Data More specifically, I am leading research theme B: Big data analytics for image processing. The research profile, Scalable resource-efficient systems for big data analytics, combines existing expertise in machine learning, data mining, and computer engineering to create new knowledge in the area of scalable resource-efficient systems for big data analytics. The value of the new knowledge is demonstrated and evaluated in two application areas (decision support systems and image processing). Currently, the group is collaborating, research-wise, with two companies, namely SONY Mobile (Lund) and ArkivDigital (Stockholm), by addressing practical industrial problems. I am also collaborating with GKN Aerospace Sweden AB (the world’s leading multi-technology tier 1 aerospace supplier). My research interests fall into the following disciplines: Computer vision, 3D reconstruction and Optical projection tomography, Steganography, Medical image analysis, Quantitative imaging bio-markers, Pattern localisation and recognition, Characterization and validation of imaging bio-markers, Evaluation of the association between image-based phenotypes and genomic biomarkers, Algorithms for the computer-guided analysis of multi-dimensional microscopy-data sets, Computational support for tissue-related target/ biomarker discovery, development and analysis, and machine learning applications. More info is provided in my CV.

Projekt och publikationer

Senaste publikationer
Hüseyin Kusetogullari, Amir Yavariabdi, Abbas Cheddad, Håkan Grahn, Hall Johan, "ARDIS", Neural computing & applications (Print), ISSN 0941-0643, EISSN 1433-3058, Springer Nature Switzerland, 2019
Siva Krishna Dasari, Abbas Cheddad, Petter Andersson, "Random Forest Surrogate Models to Support Design Space Exploration in Aerospace Use-case", IFIP Advances in Information and Communication Technology, EISSN 559, IFIP Advances in Information and Communication Technology, Springer-Verlag New York, 2019
Rafik Bouhennache, Toufik Bouden, Abdmalik Taleb-Ahmed, Abbas Cheddad, "A new spectral index for the extraction of built-up land features from Landsat 8 satellite imagery", Geocarto International, ISSN 1010-6049, EISSN 1752-0762, Taylor & Francis Group, 2018
M. Akser, B. Bridges, G. Campo, Abbas Cheddad, K. Curran, L. Fitzpatrick, L. Hamilton, J. Harding, T. Leath, T. Lunney, F. Lyons, M. Ma, J. Macrae, T. Maguire, A. McCaughey, E. McClory, V. McCollum, P. Mc Kevitt, A. Melvin, P. Moore, E. Mulholland, K. Muñoz, G. O’Hanlon, L. Roman, "SceneMaker", Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, ISSN 1867-8211, Lect. Notes Inst. Comput. Sci. Soc. Informatics Telecommun. Eng., Springer Verlag, 2018
Spjuth Ola, Karlsson Andreas, Clements Mark, Humphreys Keith, Ivansson Emma, Dowling Jim, Eklund Martin, Jauhiainen Alexandra, Czene Kamila, Grönberg Henrik, Sparén Pär, Wiklund Fredrik, Cheddad Abbas, Pálsdóttir þorgerður, Rantalainen Mattias, Abrahamsson Linda, Laure Erwin, Litton Jan-Eric, Palmgren Juni, "E-Science technologies in a workflow for personalized medicine using cancer screening as a case study", JAMIA Journal of the American Medical Informatics Association, ISSN 1067-5027, EISSN 1527-974X, Vol. 24, nr 5, pp. 950 - 957, Oxford University Press, 2017

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