Masoud Abedi
Research Associate in Thünen Institute of Baltic Sea Fisheries
Forschungsinteressen
- Machine Learning
- Data Mining
- Optimierungsalgorithmen (Multi-Objective, Query, Multi-Objective Query)
- Komprimierungsalogorithmen
Projekte und Aufgaben
- Entwicklung von Anwendungen zur Datenkontrolle und Qualitätssicherung in der kommerziellen Fischereibeprobung im Rahmen des DCF
- Entwicklung von neuen Methoden und Anwendungsmechanismen für wissenschaftliche Forschungsdatenbanken.
- Entwicklung und Implementierung von data mining Methoden zur Analyse von Fosrchungsdaten und der Entwicklung von Vorhersage-Tools für marine Umweltvariablen
- Programmierer in C, C++, C#, Python, Matlab, FORTRAN, and Java
Publikationen
- Abedi M, Pourkiani M (2020) AIMCS: An Artificial Intelligence based Method for Compression of Short String. In: IEEE 18th World Symposium on Applied Machine Intelligence and Informatics (SAMI 2020), January 23-25, 2020 in Herl'any, Slovakia.
- Shekarchizadeh N, Abedi M (2019) Determining the constitutive parameters of a macroscale second-gradient model for planar pantographic structures by using optimization algorithms. In: Gleim T, Lange S (eds) 8th GACM Colloquium on Computational Mechanics for young scientists from academia and industry : 28-30 August 2019 in Kassel, Germany. pp 31-34
PDF Dokument (nicht barrierefrei) 3779 KB - Pourkiani M, Abedi M (2019) An introduction to a dynamic data size reduction approach in fog servers. In: 2019 International Conference on Information and Communications Technology (ICOIACT). IEEE, pp 261-265, DOI:10.1109/ICOIACT46704.2019.8938494
- Pourkiani M, Abedi M, Tahavori MA (2019) Improving the quality of service in WBSN based healthcare applications by using fog computing. In: 2019 International Conference on Information and Communications Technology (ICOIACT). IEEE, pp 266-270, DOI:10.1109/ICOIACT46704.2019.8938448
- M. Abedi, A. Malekpour, P. Luksch, M. R. Mojtabaei, A Method for Compression of Short Unicode Strings, 3rd International Conference on Computer Science Networks and Information Technology on 26th - 27th August 2017, Held at University De Québec, Montreal, Canada ISBN: 9780998900032
- M. Abedi, N. Ghasem-Aghaee, Presenting a method for Dynamic threshold value in Fuzzy-Based Pareto Optimality NSGA-II, the International conference in new research of Electrical Engineering & Computer Science, Tehran University, Iran, August 2015
WISSENSCHAFTLICHER WERDEGANG
Seit Apr 2018: Doktorand an der Universität Rostock, Deutschland
Jan 2013- Dez 2015: Senior Programmierer bei Rayan Tahlil Sepahan Co., Isfahan Science & Technology Town, Isfahan, Iran.
Sep 2013- Sep 2015: Masterstudium (M.Sc.) in Computer Engineering – Software an der Sheikhbahaee Universität, Isfahan, Iran M.Sc. Thesis: Dynamic tuning of threshold selection in Fuzzy-based Pareto in NSGA-II
Jan 2010- Okt 2012: Bachelorstudium (B.Sc.) in Computer Software Technology Engineering an der IAU Isfahan (Khorasgan Branch), Isfahan, Iran
Jan 2007- Okt 2009: A.D. in Computer- Software an der IAU Khomeinishahr (Isfahan), Isfahan, Iran