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165 days remaining to submit papers to MIC-Green 2020 in Istanbul, Turkey
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Summary Information of Prof. Abdulhamit Subasi
Name Prof. Abdulhamit Subasi
Affiliation Effat University, Jeddah, Saudi Arabia
Topics Machine Learning
Artificial Neural Networks
Biography Abdulhamit Subasi received the B.S. degree in electrical and electronics engineering from Hacettepe University, Ankara, Turkey, in 1990 and the M.S. degree in electrical and electronics engineering from Middle East Technical University, Ankara, Turkey, in 1993. He received his Ph.D. degree in electrical and electronics engineering from Sakarya University, Sakarya, Turkey, in 2001. In 2006, he was senior researcher at Georgia Institute of Technology, School of Electrical and Computer Engineering, USA. He worked as a visiting Assistant Professor at International University of Sarajevo, Sarajevo, Bosnia and Herzegovina from 2008 to 2009. He is appointed as an Associate Professor of Information Technology. He worked as a Dean of Engineering Faculty at International Burch University, Sarajevo, Bosnia and Herzegovina from 2009 to 2013. He is appointed as a Professor of Electrical and Electronics Engineering at International Burch University, Sarajevo, Bosnia and Herzegovina at 2012. Since 2015, he is working as a Professor of Computer Science at Effat University, Jeddah, Saudi Arabia. His areas of interest are artificial intelligence, data mining, machine learning, pattern recognition and biomedical signal processing. He has worked on several projects related with biomedical signal processing, pattern recognition and computer network security. Moreover, he is voluntarily serving as a technical publication reviewer for many respected scientific journals and conferences. He awarded with Queen Effat Award for Excellence in Research, May 2018. He published the book “Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques, A MATLAB Based Approach” with Elsevier, ISBN:978-0-12-817444-9. Another book “Practical Machine Learning for Data Analysis using Python” with Elsevier will be published end of 2019.
User Since Saturday, 3 August 2019
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